{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Bike Sharing Dataset Exploratory Analysis\n",
    "\n",
    "+ Based on Bike Sharing dataset from [UCI Machine Learning Repository](https://archive.ics.uci.edu/ml/datasets/Bike+Sharing+Dataset)\n",
    "+ This notebook is based upon the hourly data file, i.e. hour.csv\n",
    "\n",
    "---\n",
    "Reference:\n",
    "Fanaee-T, Hadi, and Gama, Joao, 'Event labeling combining ensemble detectors and background knowledge', Progress in Artificial Intelligence (2013): pp. 1-15, Springer Berlin Heidelberg,"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Import required packages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# data manipulation \n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "# plotting\n",
    "import seaborn as sn\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "# setting params\n",
    "params = {'legend.fontsize': 'x-large',\n",
    "          'figure.figsize': (30, 10),\n",
    "          'axes.labelsize': 'x-large',\n",
    "          'axes.titlesize':'x-large',\n",
    "          'xtick.labelsize':'x-large',\n",
    "          'ytick.labelsize':'x-large'}\n",
    "\n",
    "sn.set_style('whitegrid')\n",
    "sn.set_context('talk')\n",
    "\n",
    "plt.rcParams.update(params)\n",
    "pd.options.display.max_colwidth = 600\n",
    "\n",
    "# pandas display data frames as tables\n",
    "from IPython.display import display, HTML"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Shape of dataset::(17379, 17)\n"
     ]
    }
   ],
   "source": [
    "hour_df = pd.read_csv('hour.csv')\n",
    "print(\"Shape of dataset::{}\".format(hour_df.shape))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>instant</th>\n",
       "      <th>dteday</th>\n",
       "      <th>season</th>\n",
       "      <th>yr</th>\n",
       "      <th>mnth</th>\n",
       "      <th>hr</th>\n",
       "      <th>holiday</th>\n",
       "      <th>weekday</th>\n",
       "      <th>workingday</th>\n",
       "      <th>weathersit</th>\n",
       "      <th>temp</th>\n",
       "      <th>atemp</th>\n",
       "      <th>hum</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>casual</th>\n",
       "      <th>registered</th>\n",
       "      <th>cnt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.24</td>\n",
       "      <td>0.2879</td>\n",
       "      <td>0.81</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
       "      <td>13</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.22</td>\n",
       "      <td>0.2727</td>\n",
       "      <td>0.80</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8</td>\n",
       "      <td>32</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.22</td>\n",
       "      <td>0.2727</td>\n",
       "      <td>0.80</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5</td>\n",
       "      <td>27</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.24</td>\n",
       "      <td>0.2879</td>\n",
       "      <td>0.75</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.24</td>\n",
       "      <td>0.2879</td>\n",
       "      <td>0.75</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   instant      dteday  season  yr  mnth  hr  holiday  weekday  workingday  \\\n",
       "0        1  2011-01-01       1   0     1   0        0        6           0   \n",
       "1        2  2011-01-01       1   0     1   1        0        6           0   \n",
       "2        3  2011-01-01       1   0     1   2        0        6           0   \n",
       "3        4  2011-01-01       1   0     1   3        0        6           0   \n",
       "4        5  2011-01-01       1   0     1   4        0        6           0   \n",
       "\n",
       "   weathersit  temp   atemp   hum  windspeed  casual  registered  cnt  \n",
       "0           1  0.24  0.2879  0.81        0.0       3          13   16  \n",
       "1           1  0.22  0.2727  0.80        0.0       8          32   40  \n",
       "2           1  0.22  0.2727  0.80        0.0       5          27   32  \n",
       "3           1  0.24  0.2879  0.75        0.0       3          10   13  \n",
       "4           1  0.24  0.2879  0.75        0.0       0           1    1  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(hour_df.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Types and Summary Stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "instant         int64\n",
       "dteday         object\n",
       "season          int64\n",
       "yr              int64\n",
       "mnth            int64\n",
       "hr              int64\n",
       "holiday         int64\n",
       "weekday         int64\n",
       "workingday      int64\n",
       "weathersit      int64\n",
       "temp          float64\n",
       "atemp         float64\n",
       "hum           float64\n",
       "windspeed     float64\n",
       "casual          int64\n",
       "registered      int64\n",
       "cnt             int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# data types of attributes\n",
    "hour_df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>instant</th>\n",
       "      <th>season</th>\n",
       "      <th>yr</th>\n",
       "      <th>mnth</th>\n",
       "      <th>hr</th>\n",
       "      <th>holiday</th>\n",
       "      <th>weekday</th>\n",
       "      <th>workingday</th>\n",
       "      <th>weathersit</th>\n",
       "      <th>temp</th>\n",
       "      <th>atemp</th>\n",
       "      <th>hum</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>casual</th>\n",
       "      <th>registered</th>\n",
       "      <th>cnt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>17379.0000</td>\n",
       "      <td>17379.000000</td>\n",
       "      <td>17379.000000</td>\n",
       "      <td>17379.000000</td>\n",
       "      <td>17379.000000</td>\n",
       "      <td>17379.000000</td>\n",
       "      <td>17379.000000</td>\n",
       "      <td>17379.000000</td>\n",
       "      <td>17379.000000</td>\n",
       "      <td>17379.000000</td>\n",
       "      <td>17379.000000</td>\n",
       "      <td>17379.000000</td>\n",
       "      <td>17379.000000</td>\n",
       "      <td>17379.000000</td>\n",
       "      <td>17379.000000</td>\n",
       "      <td>17379.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>8690.0000</td>\n",
       "      <td>2.501640</td>\n",
       "      <td>0.502561</td>\n",
       "      <td>6.537775</td>\n",
       "      <td>11.546752</td>\n",
       "      <td>0.028770</td>\n",
       "      <td>3.003683</td>\n",
       "      <td>0.682721</td>\n",
       "      <td>1.425283</td>\n",
       "      <td>0.496987</td>\n",
       "      <td>0.475775</td>\n",
       "      <td>0.627229</td>\n",
       "      <td>0.190098</td>\n",
       "      <td>35.676218</td>\n",
       "      <td>153.786869</td>\n",
       "      <td>189.463088</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>5017.0295</td>\n",
       "      <td>1.106918</td>\n",
       "      <td>0.500008</td>\n",
       "      <td>3.438776</td>\n",
       "      <td>6.914405</td>\n",
       "      <td>0.167165</td>\n",
       "      <td>2.005771</td>\n",
       "      <td>0.465431</td>\n",
       "      <td>0.639357</td>\n",
       "      <td>0.192556</td>\n",
       "      <td>0.171850</td>\n",
       "      <td>0.192930</td>\n",
       "      <td>0.122340</td>\n",
       "      <td>49.305030</td>\n",
       "      <td>151.357286</td>\n",
       "      <td>181.387599</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.0000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.020000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>4345.5000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.340000</td>\n",
       "      <td>0.333300</td>\n",
       "      <td>0.480000</td>\n",
       "      <td>0.104500</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>34.000000</td>\n",
       "      <td>40.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>8690.0000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.484800</td>\n",
       "      <td>0.630000</td>\n",
       "      <td>0.194000</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>115.000000</td>\n",
       "      <td>142.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>13034.5000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.660000</td>\n",
       "      <td>0.621200</td>\n",
       "      <td>0.780000</td>\n",
       "      <td>0.253700</td>\n",
       "      <td>48.000000</td>\n",
       "      <td>220.000000</td>\n",
       "      <td>281.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>17379.0000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.850700</td>\n",
       "      <td>367.000000</td>\n",
       "      <td>886.000000</td>\n",
       "      <td>977.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          instant        season            yr          mnth            hr  \\\n",
       "count  17379.0000  17379.000000  17379.000000  17379.000000  17379.000000   \n",
       "mean    8690.0000      2.501640      0.502561      6.537775     11.546752   \n",
       "std     5017.0295      1.106918      0.500008      3.438776      6.914405   \n",
       "min        1.0000      1.000000      0.000000      1.000000      0.000000   \n",
       "25%     4345.5000      2.000000      0.000000      4.000000      6.000000   \n",
       "50%     8690.0000      3.000000      1.000000      7.000000     12.000000   \n",
       "75%    13034.5000      3.000000      1.000000     10.000000     18.000000   \n",
       "max    17379.0000      4.000000      1.000000     12.000000     23.000000   \n",
       "\n",
       "            holiday       weekday    workingday    weathersit          temp  \\\n",
       "count  17379.000000  17379.000000  17379.000000  17379.000000  17379.000000   \n",
       "mean       0.028770      3.003683      0.682721      1.425283      0.496987   \n",
       "std        0.167165      2.005771      0.465431      0.639357      0.192556   \n",
       "min        0.000000      0.000000      0.000000      1.000000      0.020000   \n",
       "25%        0.000000      1.000000      0.000000      1.000000      0.340000   \n",
       "50%        0.000000      3.000000      1.000000      1.000000      0.500000   \n",
       "75%        0.000000      5.000000      1.000000      2.000000      0.660000   \n",
       "max        1.000000      6.000000      1.000000      4.000000      1.000000   \n",
       "\n",
       "              atemp           hum     windspeed        casual    registered  \\\n",
       "count  17379.000000  17379.000000  17379.000000  17379.000000  17379.000000   \n",
       "mean       0.475775      0.627229      0.190098     35.676218    153.786869   \n",
       "std        0.171850      0.192930      0.122340     49.305030    151.357286   \n",
       "min        0.000000      0.000000      0.000000      0.000000      0.000000   \n",
       "25%        0.333300      0.480000      0.104500      4.000000     34.000000   \n",
       "50%        0.484800      0.630000      0.194000     17.000000    115.000000   \n",
       "75%        0.621200      0.780000      0.253700     48.000000    220.000000   \n",
       "max        1.000000      1.000000      0.850700    367.000000    886.000000   \n",
       "\n",
       "                cnt  \n",
       "count  17379.000000  \n",
       "mean     189.463088  \n",
       "std      181.387599  \n",
       "min        1.000000  \n",
       "25%       40.000000  \n",
       "50%      142.000000  \n",
       "75%      281.000000  \n",
       "max      977.000000  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# dataset summary stats\n",
    "hour_df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The dataset has:\n",
    "+ 17 attributes in total and 17k+ records\n",
    "+ Except dtedat, rest all are numeric(int or float)\n",
    "+ As stated on the UCI dataset page, the following attributes have been normalized (same is confirmed above):\n",
    "    + temp, atemp\n",
    "    + humidity\n",
    "    + windspeed\n",
    "+ Dataset has many categorical variables like season, yr, holiday, weathersit and so on. These will need to handled with care"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Standardize Attribute Names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "hour_df.rename(columns={'instant':'rec_id',\n",
    "                      'dteday':'datetime',\n",
    "                      'holiday':'is_holiday',\n",
    "                      'workingday':'is_workingday',\n",
    "                      'weathersit':'weather_condition',\n",
    "                      'hum':'humidity',\n",
    "                      'mnth':'month',\n",
    "                      'cnt':'total_count',\n",
    "                      'hr':'hour',\n",
    "                      'yr':'year'},inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Typecast Attributes "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# date time conversion\n",
    "hour_df['datetime'] = pd.to_datetime(hour_df.datetime)\n",
    "\n",
    "# categorical variables\n",
    "hour_df['season'] = hour_df.season.astype('category')\n",
    "hour_df['is_holiday'] = hour_df.is_holiday.astype('category')\n",
    "hour_df['weekday'] = hour_df.weekday.astype('category')\n",
    "hour_df['weather_condition'] = hour_df.weather_condition.astype('category')\n",
    "hour_df['is_workingday'] = hour_df.is_workingday.astype('category')\n",
    "hour_df['month'] = hour_df.month.astype('category')\n",
    "hour_df['year'] = hour_df.year.astype('category')\n",
    "hour_df['hour'] = hour_df.hour.astype('category')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualize Attributes, Trends and Relationships"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Hourly distribution of Total Counts\n",
    "+ Seasons are encoded as 1:spring, 2:summer, 3:fall, 4:winter\n",
    "+ Exercise: Convert season names to readable strings and visualize data again"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Text(0.5, 1.0, 'Season wise hourly distribution of counts')]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "#plt.subplots()是一个函数，返回一个包含figure和axes对象的元组。因此，使用fig,ax = plt.subplots()将元组分解为fig和ax两个变量。\n",
    "fig,ax = plt.subplots()\n",
    "sn.pointplot(data=hour_df[['hour',\n",
    "                           'total_count',\n",
    "                           'season']],\n",
    "             x='hour',y='total_count',\n",
    "             hue='season',ax=ax)\n",
    "ax.set(title=\"Season wise hourly distribution of counts\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "+ The above plot shows peaks around 8am and 5pm (office hours)\n",
    "+ Overall higher usage in the second half of the day"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Text(0.5, 1.0, 'Weekday wise hourly distribution of counts')]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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k2dtRORr+gwr3/REq62BtbKgIqLEe2/7KQ4qmaTidTtxuN215cajJZMJsNmO1WjGZgsmga2Bg0FZpSqHiQAmWa/S0oFVpbTegotX6Ew5RqPSxFR7bJX7Kg8ZisSCE8NmvaRpHjx6lpKSE2NhYLBaLn9ZtA5fLhc1mIz4+nm7duhmCxcCgjaN7f9VbpymFSlV+Bc90qTv1v1FAnBAiQUpZAtWG/ViUyqsqz0QXVE4IPLZrq8ROiNzcXEpKSkhJSSE5OTmUh26V5Ofnk52dTW5uLp06dWru7hgYeLHy6EoeWa0i6j807iFO72aYWJubpjTUr9L/emYTrMrtPB8ooyZHOcAkfd8WKWUWKilOdbkQYigqadNqQkhlZSVRUVGGQNFJTk4mKiqKysr68m0ZGDQ9mqbx2JrHOFZ2jGNlx3h87eNtWl3dUmiymYqUcp8Q4n/Am3paWDsq78ZCPePaa6hsdVejEjU9D7zokT3wOWCOEOIgKgHRa8CnUspDoeyn2+1u0yovf1gsFtxuI5K9QcvC6XZypLQmWebhksM43U4iLD5Zlg2akKYO03I1KuXtN6gUpQtQ61EAZqHCgH+FStX6ASqTWhXPAR1R2dEiUNnrPHOvGxgYGBg0M00qVPSUr3/RP7XLbKj0tDPraKsBD+gfAwMDA4MWSFsNKNmimTVrFuXl5Tz33HMB1b/11luJjY3lqaeeCnPPDAxaFt0LBzJp32UALO33cTP3xgAMoWJgYNBK0TSNCfsvJcGunGom7P+DYahvARhJugwMDFolbpdGO1vH6u12tk64XYZQaW4MoRIEF110Ea+++mr19iOPPEJ6ejpOpxOAnJwchBAcPnyYN954g8mTJzN8+HAuv/xyNm/e7HWshsqrsNlsXHnllVx22WWUlZUB8MUXX3D22WeTnp7O/fffj91u92rz9ttvM3XqVE455RTGjBnDXXfdRVlZGXa7nTFjxvDpp5961b/qqqsCVrUZGBgY1IchVIJg4sSJrFmzpnp77dq1VFZWsmPHDgBWrlxJ3759WblyJe+++y4PPfQQn3/+OZMmTeLqq6/m8OHDAMybN6/e8iqcTid/+9vfKC8v57XXXiMuLo41a9Ywe/ZsrrnmGubPn09sbCw///xzdZuvv/6a559/nlmzZrFo0SKefPJJFi9ezMcff0xkZCRTp07lm2+qY3qSnZ3NL7/8wgUXXBDOS2dgEHL8qbpyKnKaoScGnhhCJQgmTpzIxo0bsdvt5ObmcvToUcaNG8f69esBWL58OZMmTeKVV17hjjvu4Mwzz6R3797MnDmTkSNH8uGHHwI0WA7qgZk9ezZHjhzhjTfeIDExEVAC6ayzzuKKK66gb9++3HvvvfTt27e6XefOnXnqqaeYPHky3bp146yzzmLMmDHs3bsXgAsvvJB169aRm6sCEyxcuJDBgwd7HcPAoKWz6ugqrvnuap/9F82/kDuX3klWWVa97VceXclvP/stv/3st6w8ujJc3WyTGEIlCIYPH47VamXLli2sXbuWU089lbFjx7J+/Xo0TWPVqlWMHj2azMxMHnjgAYYPH179Wbt2LRkZGZSVldVbXsWSJUtYsGAB8fHxJCUlVe/fs2cPQ4YMqd42mUwMHTq0envMmDGkpqbyzDPPcOutt3LuueeyZMmS6sWLo0aNIjU1le+++w6Ar776imnTpoX70hkYhIwv9n7BzB9nsid3l2+h28WiA4uY/s10DhYf9NveWIkfXgzvryCwWq2MHz+eNWvWkJOTw5gxYxg9ejRvvvkm27dvx2azMWbMGACeeuopBg8e7NU+Ojq6+uVeV3kVycnJzJ07l+uvv5558+Zx+eWXV5fVfgAiIiKqg7zNnz+fhx9+mN///vdMmDCBm2++2cteYjKZmDZtGgsXLuSMM85g165dvPLKKyG4OgYG4Wd73nYeXvUwGhoq8IZ/cipyuGXxLcy/aD4RZu8V9sZK/PBizFSCZMKECaxevZpNmzYxevRohg4dis1m46233uL0008nISGBTp06kZ2dTa9evao/77//PsuXL2+wvIphw4YxatQoZs6cydNPP01OjtIVCyHYsmWLV5+qbDoAH3zwAddddx0PP/wwl156KUIIDh486CWILrzwQjZv3sznn3/O2LFjjUCRBq2Gd359B5fWcE4PgAPFB/jp0E9+y7oXDuSKDQ9xxYaH6F44MJRdbPMYQiVIJk6cyNatWzl48CDp6elEREQwfPhwvvnmGyZOnAjA9ddfz0svvcTChQs5fPgwL730Eh988AF9+vQJqNyTa6+9luTkZJ544glAeWotW7aMt956i4yMDJ555hl27apRAyQlJbF27Vr27t3Lnj17uP/++9m7d6+Xh1i/fv0YOHAgb731lqH6Mmg1FNmK+OHQD0G1+d/u//ns81zfkmBPNta3hBhDqARJSkoKffv25ZRTTqlWV40ePRpN06qFylVXXcW1117Lv/71L8477zy+/fZbnnvuOUaOHBlQuSeRkZE8+OCDLFy4kGXLlpGens6zzz7LJ598wkUXXcS+ffs4//zzq+vPnj0bk8nEJZdcwowZM7Db7dx0001esxmgWpicffbZYblOBgahJqMoA6fbWb3doayHT530zN8Sa0+s3t5TuMenjrG+JbyY2qKE3rBhQ6HFYmmXnp7uU3bwoDLu9erVq6m71aT84x//IDs7m6effrrBum3lmhi0bDYd38RV316F1RXJ5L1X0C/f9/kFcJmcrOr9OdtTV5AcnczSy5Z6lVfabLzxN2+Pr+uePZ3oqJAnkT3p0JN0FY0cOTKprjqGob6NsXXrVqSUfPzxx14LOQ0MWjpd47pidpuZKq+jR5Gyg7gcB3CUK5VYROzZWCJ6Y9GsTMi4FJNmIr//PtyaG7OpRinjbyDdFgfX4cJQf7Ux1qxZw+OPP8706dMZNWpUc3fHwCBgUuJSOMd2ebVA0TQNZ/licJeAuwRn+WIv4TDu4MUU5Zdx9bdXs7dgb/X+0vJCn2NvyvzFECwhwhAqbYwbb7yRzZs3c+eddzZ3V0JO6fIV7JkyhT1TplC6fEVzd8cgxGiaxoCjYzz2uNHcRTXl7iKgJpmcRbMy6Ph4Nuds5tKvL+WFTS/w0uaXuGjBRT7HvuWnW/jDV39ge952nzKD4DCEisFJgaZpZM2ZgzPzGM7MY2Q9+qgx8jzJKMwuxxZkFJa+ecMAtTblla2v8PKWl6l0+U+NvbtgNzO+m8HWnK0n2tU2jSFUDE4OHA6ySuNZOfZRVo59lKySOHA4mrtXBiGkosTecKVaxDgSgjuHs4LbltyGzWUL+lwGCkOoGJwUaJqGTLsMW3QytuhkdqddZsxUTjKskZag28RFx5IYmdhwRQ+Olx/n+wPfB30uA4UhVAxOCtwujcqYmsgAFTHG2oOTjeQucUSYnQ1X9KTczP2J/8ak1YR0MWm+r73Eyo5e2wv2LWhUHw0MoWJgYNBKMOOiS/baoNq43bD/qwp+t+12Opf0RBw/jT9uvd+n3qW/zua8nTeRUNkBgKMlR0PS57aIIVQMDAxaBbY9e+i+dyFWR2nQbTuX9eR3v97O5H3TiXe091unZ+Fgfr/tNpIqOmMxB69qM1A06eJHIcR4oHbygjIpZbwQwgrMBabr/XoPuFNKafdoPxv4K5AALABukVL6Op23UFxujU2HCjhWVEmk1cwp3drRLSkm7Od1Op089dRTfP3117hcLi666CLuvvtuIiMjw35uA4NQoZWXE20rZNjWl9ly6l9wWH2fHU1zYDJZiKoswB6ZgGauecWZ6olqXEWMM4Fzdl1PzoB1Ie17W6KpV9QPBrYBv/XYV+VY/gRwLnAhEAm8A9iBOwGEEDcDtwJXAXnAq8DrwB+aouMngt3p5u1VGbyz6iBHCyuq95tMcGZaJ26Z0p+RvZLDdv6nn36a5cuX8/LLL+NwOJg1axYRERHcc889YTungUGosSSrZ6RdyQEGbfsXG/ue4lPHXvQaHSuiGbZvO87I9uwe8EcKkgcFdZ6kyhSGcXFI+twWaWr11xBgu5Qyy+NzXAgRDdwM3CGlXC2lXAr8HzBTCFE1HLkDeExKuUhKuR64GrhECNGzib9DUFQ6XFz79i88sXCXl0AB0DT4Webwx1fWMH/jkTqOcGLYbDY++ugj7rnnHoYPH86YMWO4//77mTdvHpWV/v31WxuHV+7km/t8Daurnv+e8rySZuiRQTiI7BhNZIKD4wmxbOiVgEs77KeWg9yYEtb2T8XqyCN96wuk7f4o+JPtbHfC/W2rNIdQ8ZOujXQgDljmsW+pvi9dCJEK9PUsl1JuAwqA08PW2xBw7/xtrNibW28dl1vjrs+2si4jP+Tn37lzJ+Xl5YwePbp635gxYygvL2fnzp0hP19TomkaSx77gi/fO8aRSt+cMNsy4vnwnp/IXCOboXcGocZUdBhzfxebeqXgNtf/6iqNjmRD71QAYirygj5XwbGyRvXRoOnVX0OAUiHEFqADSnDcAXRD2VaqYy5IKYuFEOVAd5QaDKC2S8YxvTxoXC4XUvq+bCorK0lISAjJKH5/bhmfbwrMi8Tl1nj2R8kbfx5+wuf15MiRI8TExBAREVH9naxWK9HR0Rw+fJhBgxpWDbhcLkpKSlrczObAhxvYm51ave0vuKDNmsDXr+9mdEkesT07NFdXDUJAdO5hdscn4yoObCxcGBdNTkIsjTG5O4qK/L4f2jpVGWbro8lmKkKIdkBXIAK4HrgS6AN8B8QC/paw2oAovRw/darKWySfbsgMqv7Kffkcyi8PaR8qKir8GuQjIyO9Ene1Nmx5Jew/ViMk6gsu6LDGsf9z37waBq2L8sgUdpV0DqrN8f7RJFjq1xT4I6Y0K+g2Boomm6lIKYt0wVImpXQBCCF+B2QCFfgXDlFAuV5etV3ipzxoLBYLQgif/VW5QzzzxTeW7ceCd32UOZWkdQ2d0T4hIQGHw+HzfRwOB4mJiQF9T4vFQlJSUovKp7Lyyc9xmz313nUFF1Tj1OPOVLondSYuxb87qUHL59hecGrBzTvyzbH0GbSFXwt3U5iUFnC7HgUbEeLaYLt40qPnU6m3TpPaVKSUxVUCRd/ORnly9QfihBDVgXqEEImoGcpRoMqK3aXWIbvgqxJrMdicgeXS9sTudDdcKQhSU1MpLy+ntLRGwJWWllJRUUFKSkpIz9WUHMmoaLiSB25zBAe+3xSm3hg0Ba5GxHJzaWYsVo2ehxcH3Ca6IocU58Ggz2WgaEr111ghRImnt5b+f0dgNVAGTPBoMknft0VKmQXs9ywXQgwFkvS2LZLOicHPdjonhlabN3DgQGJjY9mwYUP1vnXr1hEbG8vAgQNDeq6mxOEK/ta1FYZWtWjQtMQnd2y4Uu02VhvR7R10KtxKr4OLGqxvdZRx6q+vEt8ruECUBjU0paF+E0rV9aYQ4nYgGngOWCKlXCqEeA14QQhxNWACngdelFJWWYefA+YIIQ4CWcBrwKdSykNN+B2CYtqwrvywIzvg+p0SojitT2iNydHR0Vx66aXMmTOHf/zjH2iaxmOPPcb06dOJasXpU4OOAQVEJbTe72sASSmpdOkvOLY3cAP6wCkXYLGbSOy5j74ZXxJlK2B/7/Nw+gsyqblJ3/Ic8WWZtO9pBBtpLE1pU7EJIc4FnkZ5fZmAL4G/61VmATHAV4AT+ACY7XGI51CzmrdRxv6vUWtbWiznDEklJTGK7OLAwmhfcVpPIq2hv5nvvPNOKisrmTlzJhaLhWnTpnHbbbeF/DxNSbceVnI9/CA0rX7ViNllp/fZI8LcK4NwI35zVsBCxRoVxSm/vwGyh9FRXkbJkRi6Zy4nNWstyyY+49vAZMYWlUxJp/1ERwc+GDTwpkldiqWU+8H/UlUppQ2YqX/8lWvAA/qnVRBpNfPMZelc/eY6HA1EzB3RM4mZk/qFpx+RkcyZM4c5c+aE5fjNQeS0zphfsuMym3BWrMFl2+JTx1Y8j4iYcVgi+xLh3EJs16nN0FODUGIelEphuwSSihpe1Dpq2u+JTWwHORYiE1x0n5DPkeXJmOuxde7uNYRDo9cxxhIRym63KYw5XpgZ368j78wYQ8f4ulUvZw9O4Z1rxxAdYQSxC5Qvy+v9/HEAACAASURBVH6iWPsCe8knuGy/ULOUyQN3No6yL9DKVrJg0FfsyNvR5P00CC37izMo6zACc2TD66v2/bIGt9sFnQeDyUxcZzt9fptDQp+6FzYWtz+FlQnRaJ2HhLLbbYqmXvzYJhnfvyMr7pnMt78eY8HmTLL0gJJDu7Vj+mk9GdLVCAkRLBnFGXSMOUbPktgG69rsa7GbbWQUZzCko/GyaM3sK9pHh4rumK0RuO31R4TIOZjB1h++I33q+ZB2LshviExw0WVEMdSxdCXKlYTL3ouDQ86nd+i73yYwhEoTER1h4XfDu/O74Y0KAGBQi5h8Fz2PNyxQqjh1XzsjE+RJQEbeAQZXDsfpWO+3vPfQdA5s21y9vfLj90gbdwaxZ/wddn8LmrvBWMW9CoawzqoZQqWRGOovg1ZJ7wPBeXKl5kfTsTz8aQYMwktOZjEmzYzb6d/pc+Kf/ozFWjNWriwrZeW896DHGJj2LAQQ/r5/zhDWZv0Sqi63OQyhYtAqSSkNfJZSRVKRMTFvzZTaS9HyI9FcOaD5j0PXvls3Rk37vde+rT8tInv/XhhxFVz5P+gyDJfjAJVFr1FZ9BouxwHvY1T2ZOuh7bi10C5EbisYQsWgVRJrDn7W4Q4gGJ5ByyWjKIPksi51zlIATCYTp138R+I7eCyU1DQWv/kymtsN/c9C+/MXPnHiosqP1xwDM4nHu7KnwIgX1xgMoWLQKknoGPzq6sSOvuHxDVoP+4r2kVzeFbejnvXOlggioqM588/Xee0+tkeyY/nPgBpc1I4T1yF/m1f9fjlDWJdlZH9sDIZQMWiVDJowOaj6CR070W2Q4fnVmtlfuJ+OpZ1xO+sJ92dSNpO0sWfQY8ipXkXLPngLW7l/d+JOpb96bXcvGsi6o4ZdpTEYQsWgVdJvxBgSOwYeBn341Aswm411QK2ZjJxDRNsqgYYDS5pMJqbMuAmTRzKv8qJCVn/2IWaLr7G+R+I2LK6ayBcWYji8JxenO/hwQG0dQ6g0NbZSyNsHRUfAbej4G4vZYuHUYeehIvbUT49BpzLivIvC3ymDsJJ/pMxH9WXxMKYnpXTBbKlxxujYoxfDz5nmVX/jt1+Rl33M59hJXUtJzvde95Ka3cdYMNsIDKHSVGQsg3lXwFM94fkR8MwQeHoQ/PQ4lB5vuH0I0DSN66+/nvfff79Jzhduyo64iUy4FEx1e4KZI4YwYvRFXm6mBq2Pckc57rwIXLWM9P0sFSR26kxip86cde1MTCbvWcj4S6cT2y6peltzu1n2wds+x4/rZKdTkbddpX+uYVdpDIZQCTeaBotmwzvTYNfXoHnMTkqzYdk/4cXT4HB49bdut5tHH32U5cuXh/U8TcnxbBdmayqWiLqTL1ljRpC/L/jMfwYtiwPFB0gu64zm9J5lDO3XgRteeJMbXniT3ukjfdpFxcYxYfo1XvsO79zuU88Um0yvqA1e+2JcqWza41vXoH4MoRJulv4TVr9Qf52KfPjgEqUWCwOHDx/myiuvZMmSJSQm+gn53QpxOpwUuFUWR7er7pme25lN/pGGgw8atGz2Fe6jc34EKpunwuoykTp6dINth0ycQpcBvllePdlhHU9S6nESSryTc5XscWF3td60282BIVTCSelxWPavwOpWFsGSJ8PSjc2bN5OWlsb8+fNJSDg5kg8dW7ULtyUSTXOj1SNUNGcWhUVGeJbWzv7C/SSUeidZSy53EJXesBegyWxmyoyZ1Z5h/vh+fSHzKk4lqniN1/4BmYItOb4RsA3qxhAq4WTju+AOIgXqjgVQFnpVzbRp03j44YdJSkpquHIr4cgv+wHQ3Hmo9Dv+cbuyKHYlGHG/WjkHMzPB4a366mbPw9TllIDad+7Tl4QO9a9tqnBFcjTmCC57jcagfWV/1oVZNX2yYQiVcJKxNLj6LjscXBWevpxkZB8sBZR6qz40Vy52SySlWYVN0S2DMFF8sMRnRtoj3gmRgYXr2bZ4ESW5OQ3W00wmHGXfomlK5WUyRbB7a2YDrQw8MYRKOLE1QpffmDZtDE3TyK2IU/+7GsrQ50Zz5XB8497wd6yFUrm7gGNPrePYU+uo3F3Q3N0JGpvLRuwh7xm/VYsmuW/XgNprmsam774O4ox2XB5h9WNkDOWO8nrqG3hiCJVwEtO+adq0MQr3ZGKzKttQQzMVVSeLnB1Hwt2tFommaRR8sRdXoQ1XoY2CBXtbnSrwQNEBOtSShfH2CKIGB6b6yj10gLwj9YR28YPLvqv6/65Fg9mQvaGe2gaeGM774STtHNj3U+D1I+Kg9xnh689JwsFlOwALmuZSEWs9iLfaKNcsuF01t7bblUX+vjZ6q7s0XPk1EX1deZXg0sBafwj4yt0FFMxXARXb/34A0WmBDXYa264+9hftJ7as1Gtfh5JKokdMDKh9SX4j7JSuGo2BxdSO9b/+yoTuE4I/ThvEmKmEk2F/UoIi4PqXQfTJ4fIbTo7JPAA0Vx5Qs+4nyuzkxv7rGN/dO7qs5symsCIWHP7DpRt409jZTbhmRXszfsXs8lYLdys9hmXQ6QG1t1iDzzdv1ryjXeRuan1qw+bCECrhJLodTH08sLqJ3WHSrPD25yQht0Ddtm5Xltf+lOhSTCYYHFnktV9z51Nk7YiWsaLJ+hgOmsw2UtfsJlztGiB38wGvbbO5A53iijHFBObN2KlXH8yW4OK+JTi9+518KIUiW1EdtQ08aTadgBDiCWC6lLK3vm0F5gLT9X69B9wppbR7tJkN/BVIABYAt0gpW7Zbz6gZ4KxUq+q1OmJ9JfeFKz6DhJSwd+enn4JQx7VAKgtLKbYkA2oG4klKjBrNJlgdOCIdRNhrRqgOiijOKKJd3YvvWzSeswCAggV7Sb1zlE9YkpOSDG8BGu1OIrpn4MFEYxPbMWDMeOTqwKNJDDUdxtORONrdizX71zN10FkBH6Ot0iwzFSHESOCuWrufAM4FLgQu1v8+4dHmZuBWYAYwGRgMvN4U/T1hxv4F/roOxt4McXpOD5MZuo6AC1+Av6yCDv2at4+thMNLflXXDnDX8vxKia7Ru5sSvL11NFcW2RmtOOJsmGYBLR27005svvdvmVhpJiptQFDHGXPxpQHHf+vZNYEhKXuI8UjchcnM9jVG0q5AaHKhIoSIBN4GVnnsiwZuBu6QUq6WUi4F/g+YKYSoSvF3B/CYlHKRlHI9cDVwiRCiZ5N+gcbSsT+c8yTctRceyIUH8uDGn2HEnyHCyJ0eKEc3Ky8uTXOiubwNsKnRNXr35BjvvBluZza5+fHh72CY8GebCNTO0Zh2TU1dqr3tu3/B6vQcDJjpUFJK9LDTgjp+5959Of/WuxsULB269+SCm2YS29FBcpF3jhX31lY8KGlCmmOm8iCwF/jUY186EAcs89i3VN+XLoRIBfp6lksptwEFQGDWupaEJQLMhjmrMWRnqfUKyuurJg5UtMVBYkRNPoy+Ud76b7cri8Y4AbUUHH5mJf72VaFpGpV7Csj5YKdPWen2PDR3yxEs9Rn4d27yXgxssqSSWJZF1Oizgz7PgNPG86dH/kkfP4Enq0gbdwYxaRMwJaTQ1VorwGRZH46XNryAsq3TpDYVIcQI4EbgVOAPHkXdgDIpZfWbQEpZLIQoB7oDVXaV2infjunlQeNyuZBS+uyvrKwkISGBykrDU6gKl8tFSUlJs18Tl8tNgSsJLL7rU1KjS7xCO6VbC9nsWcFdQm5Bud/fvDXgsLupbZbes2cPEZF+BidOjajlxVgP2HzLgOJ5kvzlGdgmJ0KEn/Y2N7V9Fvd9txVXn+i6XZHdGpb9lUTX2n3w5XU4B8Xi6h5Zd+wtl0ZcLdXe7p0SLCaObN6Gp4ndHNGTJNMv7CmohILG/ZaDLvwjGZv9rzv5delPdBg6kpSUcaR1+J6NzkpcVv1bmWNYsPA7Jg4b06jzngy4XA3ngGqy4bKH2usuKWVWreJYwN8TYAOi9HL81KkqN2gDlO7IxGVRP3ftlfSe9hSADmYn9kjvB6AUW4tU/YQUrX6BUoX1qJ3on4qg1ozFuqeC2M98p3TRK0qI/SQXyz4/Awubm+jvCole7hsNwnrUQfSPRUT9XAzO4K692+XClOnthxOttSe2Q/heWyXHsyjOyqS020QSU8pJKtzlVe5eloX7+htwX38D2sZNYetHa6YpZyoPAEellO/4KavAv3CIAsr18qrtEj/lQWOxWBDCNxz2wYMq9HV0dO0xV9vFYrGQlJREr169mrUfaxfuoWp84WOkjyn1qe9ILCUyt131ttOdRydLOzoM6BLWfoYazeGmaGM2pXi/7Pv16ENMkvd9WrmngNwDgaloLJkOetiSiU1XnlSlK49SuKLuiM8mm0b0smKSkjsTP1ZdQ83lJufVbdiz6w+caj1oI2GzRvJ04eOxpjndHMW7z2lpaWQd2IPZ6fY8CokVTmLT+tHbz7MbKC6ng4X1lFccOUD3P14Bqx8gic3kkV5dZirrw8p+twJwyrwfOe1Pl7UNDzydzZs3NzhbaUrF/pXAZCFEqRCiFOU+3FP/PxuIE0JUx2UXQiSi3iBHgaoYG7XfBl3wVYkZnKRkZRQDoGkOfeFjDZ5G+ioS470FjebM4vimjPB1MAyUb83hyBNrKf3cN3ZZzj9/oXjJYa/ZV+lq31S59VFV35FVRuHX+wNqU/jlXhzH1ViufONx7AeLA2pXsS0X277A13oc2Oo9EzBbu5FQlkX0kGEBH6Mx7Fq5DM0SCf2nIBK8Mz86opKxRavPjqTJaHYj10ptAhYqQoieQggfkSyEsOguwg1xJnAKyiifDjwJZOr/rwfKAM84CJP0fVt0ddl+z3IhxFAgCVgd6HcwaN3klqtZijLS17xIYy124q2+D3evKO+XnduVTc7ehmOFtRRKN2ST/+EuTBX+vY7Mbij+7gB5X1elAdCo3JXnt25d2A8WkzV3PTlv/up5SevHDYXf7Kd8aw7FPwUXU6tsdeARf/ds8Q45b47oSVxZJlGjzgzqnIFg8nCcKcnL4ciu7SDOp2dqFvG1EndVURHTCXcbcOsOlmDUXxlAKlB7bt0TWE6N3cMvUkqvX0YIkQs4pZR79e3XgBeEEFcDJuB54EUpZZUS9zlgjhDiIJAFvAZ8KqUM7q42aJUUZmRTaVUhbNxOb5NcakyJXxvw0Igi9qFuJgC0Co5nBvfSbS6cRTbyPttNIOvAK1dmcjyrDFduhadDXODnyqlouFItbLIAmwx+Vb+/SACuSl+hWbI1m7y93plQzdaeJFT8QOSQ0BvKe5863Mt4v3PFEnpceQWWaDNx9m2U0ryq39ZEvUJFCHEtMFPfNAGLhBC174BU4EAI+jILiAG+QmVd+gCY7VH+HNARZeyPAL5GrW1pFeRW5PK/3f/j24xvOV5+nAhLBIM7DObStEuZ2H0iVnP4zFtZWVk88cQTrF27FqvVyqRJk5g1a1arSi18aGlNrvD6Fj160sflwGU1YfUwEOeXto4YTgcXHyQqiEGwPQi1UnOiOdy4bU7MUVY0TaN0ZSZF3x/wqVf8yV7O63I963MXkVWRAaZozOYOJMUWYooIPpZXQww8fZKXUNm9ZgVTZszE2nMcHTI2kM0F/r/Pye740QgaepN9jHLZNQGjgMWA5xOs6dufBXtiKeULwAse2zaUAJtZR30NZex/INhzNTdf7fuKR1Y/gs3l4ZHjgBVHV7Di6AoGJQ/i+SnPkxIX+jAtLpeLm2++meTkZN59911sNhsPP/ww99xzDy+//HLIzxcuju3MAVQ0Ap/wLHUIFQtgiy/HWlizuLTCVYLT6cJqDS4WVFNTuSXnpHVrzPrnemKHd8Ztd1G+rrYjaA1x1nZMSPkDK49/TpbDRGxFLnE96s/eGAhmi5V2KakUZatzJ6V0of+YcUS8EYOjUs3abGVlZGxez4CB5zN8+4PszS/GHuk7CHO6XYRexLVu6hUqUsoyYA6AEOIAME9/+RsEyHcHvuO+FffVW2dn/k6u//563j/vfdpFtau3brDs2LGD7du3s2LFCjp1Ui/l2bNnM336dIqLi1vNbOV4vgksoGl2NHe+V1mKHyN9FZbkfCjsVr3tch+nQGbSaUiPsPU1FMTbXHgo7gLGjYY5iHb/pZLfnNWXAauy0SoaXoNQjdVMVJ9E7IdK0GxBtAPcZQ5KVwTmX2M2mRnb6QK+y91JfGEmUSMHBXUuf5hMJn5z7V/44fUXATjr2plERscwYPRYdiz/ubreruVLGDDjcpLi7yX6iMQeOdrnWAsfX8bIS9PpNaJLm/ICq4+AdS5SyneEEMN1o3wEte54KeVLoe5ca6fcUc6c1XMCqnug+ACvbH2Fu0ffHdI+dO/enddee61aoADVN7/N1jrGB/aSCorNVUEkvV1e46024iPqdmftGleCpwjSnNlkb97f4oWKEwKyp3jyFBUsxcHDxHJaAI/2DlzMw877i3dxvTmKa4KYG5WO6kT3i9MoXXeMwvnhzaoZYY6ib1x/XEe/Jyp9nFdZY/O39E4fyQ0vvOm1b9AZZ3oJlX0b12GbeSv5kWdTGu8/IVhWYTTfvLaLtH67+M0dkzGZDcESjPfXbGAD8BRwNyogZNXnzrD0rpWzMGMhJfbA0wN/seeLkKctbd++PRMneiczevvtt+nVq5eXoGnJHF5aXxBJj+sb5xu5drClGO/b3MGRnYG5zjYn+0zBWdxL0PgOByXAA5SznvrjVO3Axd2UV9f6n9tOcYDuXwW4eVdPmhU3IoWIHgkNtFCY20Vi8reCPwB6RscRX5ZJ1IgaB9FQ52/pOTSd2HY1cQtcDgdbFi3mq4xrcFvrj8+3ex8sff7neuu0FYL5ha8HHpBSdpRS9qn16RuuDrZmFh9aHFT9EkcJ67PXh6k3ildffZXvv/+e++6rXyXXkjiy6XD1/76eX1X2FBOc9y9o11PlptFJczjQLN5a7+zslr+0aVdKcBaVxRYXT/8pnYvTu1IO3E45D1PONj/C5R9UcDNlFHoIkQI0ZlFOeQOCpRSNWVTw2Y4sXG4Nk9XMokHx/NqAEFuJgy3ndKfL7NNImBL8LDHGDAmOLKypqTU7Qxy52WyxIMZ7Z3fcsOBrHJZ6HVur2b7DTXFmy87E0RQEI1Q6AJ+EqyMnIwWVwXsaNaZNoLz44ovMnTuX++67jzPPPDNs5wk12Zk1aro6w7N0GQZDLobbtsHt26GjWnHd3u3GFu29hqWkonkf/ECSbU3oGrhtrRyN2NO7cGF6N2afP5j4KCtu4Eec/J+fgBPf4lDqNZOJCQM6khCtVGVbcXETZazGV53oRmMlDmZSxnZc2F0af/zvKu76dAsPfi/5K+U8ga9r8nqc3Es5s6jgtvlbOW5zEjss+BmypkH7ju6w2y0GnXGm13Z5RSaa278jiA8mMxvfWxn6TrUyghEqnwFXhKsjJyOxEYGNcDyJaWCa3Vgef/xxnn/+eR566CGuuuqqsJwjHLhcbvKd6gWruSvR3N4CoVqo9KmVr7x7jVHV1c7bsG93F+CwN08Y80BUNmUbs+m0MbD1NJVoPBPv4pLJKh9Pp4QoXrxiBJHW+h9ti9nEf/6UznvXncbyuydX78/Azb1+hMN0SrmHCg54LITZcKiQTzeoYBcu4Hs/wuhOylmOEw2odLiZ8/UOvjmYR2XAKy0VFQ4b0f37BNWmMaT2SyMp1Ttwh8seeODKQ3uNmUowQqUCuFcIsV0I8YUQ4hPPT7g62JoZmRJIoIEaLCYL6Z3TG64YJM8++yzvv/8+Tz31FNOnTw/58cPJ8Y37cFlUfCu3y9tInxhRSaxVf5H1meTdsPuo6n/jO3q301w5HN/aTOFaGlDZVMp8Cj7zTgblQsPu5yW8CgcPxju566bRtIupUfFNSuvERzeMZWg3/7Od/p3ieHvGaKYN6wpAUmwkAzrXn2smK0ghUBcLtx3j7/O3sciPAKqPuIgILH0mN1zxBDGZTD6zFZfdN31AXTiMlCtBCZVY4ENgHSqPSVmtj0EtLhlwCRZT4D48U3pOoXNs4GlSA2HHjh3897//5dprr+X0008nJyen+uN0tvwn4PDqmhdsnaovsxV6jvVu6DFT6R9RislrNYGb/av8hz5vTuyHS8j7YKdX5GAXGvdTwXST7yN2ZFJXXrr9DPp28hUII3u156v/O4OPbvBNZvXFzaczYYC3Cmr6aU2b6+5j7NiCEFQWswVbVn8Kv96P5qzbiSEUixFrCxXNdRy3K99/5VqY3KF1tGmNBONSPCOcHTkZSY1L5YpBV/DujncbrBtjjWHmML/rPk+IRYsW4Xa7ef3113n9de/sy1999RVpaS07afuxfYWooA2+OVSqPb+6jYKoWi/WzoMgIg4cZQiHg32mGDStZnScuc87BEhz48gpJ/ftX9Hs3i/MuVSyOQq+mDkent3qVfbXyf2Jiq7/ET61W5JPXCV/dolLR/XgrZUHOJTf8Euxd4dYnv1TOsv35vLvRbsbrO+PQ7h5hAoeIYaIINbVlK44iv1gMe0u6kf5Ft9ozMdf3Ez8+K7EjUzFZGmc/aV9l26k9htA1r6aAY3LvhNzTMP5AJ3WXQ3WOdkJWKgIIc6rr1xKWV806TbL7SNvp9BWyJf7vqyzTow1hv+c+R/S2of+BX/bbbdx2223hfy4TUVuWXT1XVp7plLt+dW3luoLwGyBbiPgwHL6Ohw4I9yYPez1+QXNE1hS8+Od5CqxkfvGr7jLvGeOr1PJlzh48ZIRdG8f5yMcAsJi4ihuuulKiSO46eTnZRsfZeWda8dw5etryS6sOxZYj+QY3rl2DL06xDG4azteWbqfEj+xu+oiJsLCuH4d+CUjn2U2J3/XSvibC9Ks3otw3Zqbo+W7sZn70C860ksQ2g+XkPPC5tqHBsCZVU7h/L1UbMulw58HY45sXOSEQWec6SVU3PZdaNHj63UUMLvsFAzaWmd5WyEY9dfXdXw+A/4T+q6dHFjMFh47/TH+PenfjOg8wqss1hrLZeIyPpv2GeO7jW+mHrZcig/nUmlV6wY0dwWa2zu+VZ1G+ip0u0oEYI/zXi9U6QhMnREq3HYXxYsPcezfv/iUZT27CVeh90LUz7HzNnYuH9OT809tfP4Xk8nEXCo4hptjuHmaijpfjH06xvHlLadzzTjf4IlJ0VZumtiXBX89g14dVF7ICIuZP4yscd92Akc9DPlHcPs4Gt85VfDmNaO559yBxDrLGJj5KVsOv+Jzvq8Pv8Kq4wvYlPct6woLcToC9MDSse0pJH+ebLQ6TIyf6HWdNHcRmqv+tALmss/5TWJw/TwZCUb95SWAhBAWoB/wIvBeiPt1UmEymZjaeypTe08lqyxLBZQ0R9C7Xe+weXudDNQXRDIpooJoixOs0V72Ey889ps7ZEJBTbgWt7uQ0rwi4juENiyOP1xlDnLf2IYjsw7TY6V3mJMlOHiGStJS4nnwgsEnfP51uLiUwF52HeKjuOu8QWxevcJrdrP47sm0i430qT9jfB8+WneISocSJnOp4C7UPf10LS+yjvGR1ULod0M7s//V74iz5+JvbGtzqf66HZLswlJ+zHHTVVzBqVrgM4/KHXnYD5UQ1Sv4UERxSe3p2acrB/fXrGly2Xditnb1W9/sLGX1uKXc6D7x2GStnUYn6ZJSuqSUu4E70OODGTRMalwqp3Y6lUEdBhkCpQGObq9Z6OgTRLJK9dVzLFjrWCjYrcYDLCU5B5PJ28V7z5Lwp+LR3Bp57+2oW6DUYjtO5lBBZISZF6aPIEZX30REmsk214y6s8ya//z0tYiwmOiZXPO9e3WIJaIBW4O/2U1MpP/xZ88OsTx/+QgiLaovVQLsUkpZR42wTIiy8tpVo6q91HYtWURcWd1ZJj2p4Cibo9txu1YWtCty2ZrgkpZ5Mmict/bAbduKpvmPc+a2xvPXowMwdejf6POdLIQi82MiKiS9gUFIKF2+gj1TppB9qGakW2d4lrpUXwAJKZCkvJrSnA6seBvzD20Ov/7btqcA+4HAMiMCSFzYgYemDSEtpSb8idlsxvWbHhw3aRw3abh/0wOzueHH12Qy8ejFp9AtKYZuSTHMueiUgBYQ1iUc/HH24BQ+uvE00nv4n/VNTOvE/JvHM7ynisulud1s+SE4E6zVUkZPzEQHGWTTltH4lAADfvMHrB6CXEPD7fSfsAtgT+Hv0dL/3OjznSwEY6j/p5/d7YA/Ad+GrEcGbRpN09j41Bvs7nkztqia4IC1Pb9Sq+0pfoz0nnQfDYWHSLM72Gi24Pl+zMkMf3630rV1h3b3x9lEsveU9vxptG8okzFT+sCU4BcATkrrxMpZU4JuFwwjeyXzyU3jSbvf+1Xw/W0TvYQjQFHOcQqOBZ4BEqCDM5eYRkRt1uzBRVD2JDI2jn4D+yB3HKje56xcj6NchV+KiD0bS0Tv6rICenGwfCi9adsEM1MZXeszCuiFSp51Q+i7ZtAWcdts7Ol4DrboZKrSOWruMtC8De2do0shMgG6NLBYVLerdHK5sEd56/hLyxvlTxUU9kOBz1IAEjDxyBn9mjWMemNUZnXRWzfqe2Ir91YFunFT6qgJV1PiKMBdK4VlrMkRcMBLT8xxJ5btZND53jMPzXkE3CXgLsFZvpik/O1e5eu/Dm/E5tZAMIb68C9nNWjz2B1OKmO8F+bVVn21jywnyuKC3qeDpYFbWLermABXuxys5TUvGZe7jPLiImITw2esr2+hXl3EBqDWCidVKrP75m8DCFhlFijRcb6CZkPeD4zqMBWAjXk/+JTHxsfzwNXDOfTOLnoGkRSgondgEZTronf6CKLjE6gs9Y02rrmLSMj7gcLkIdX7sg9XkLm3kK79k3zqtxWCymErhBiKCns/BDXL2QU8J6VcFYa+GbRBnA7fl3BtI31qQ67EnnQ5FSyR4LIT1/4g9uxRXvHDDv+6AzF+XD0HODHcrGsj5gAAIABJREFUsVZMlcGpYCzxvl5WTU04VWaJnVJo37U7BZlHqvdlVWTw9ZH/1tmm97ARTBIpzIncwQ32wISKhsa6nBL8KQwDzcNisUYgxp3Blh/8a/i39N1D76L9FLerCdS+YWEGXW8dHlAfT0aCyadyLrARFa34M+BTIAFYKoT4bXi6Z9BWcNpdLH9xKR/du8KnzMdIH1NlpG/AngLKMyz1VAC6xRRjNSV7FWes8V03Ekq2xQc368iI0LC0b52JhANVm5lMJtLPPjeoY6dPPZ89x0v40F7B5gbC7FefBxPjDpRTvqVW7Lcg87AMrBW2xZOkbna6Hf3ea9+hHQXkHgk8j9LJRjB3/OPAY1LK86SUT0gpH5dSng88Ajwanu6dPGhuN6XLl5N5zywOXjODQzfeSM5zz+HIDM5g2RgyMjK47rrrGD58OGeccQZz585tUXG/7JVOPrv7a7Zuc+EwRfuU+4ZnKYXYDtA5wDUcul0lzenAqnnr2I/t2+OvRch4rbgERxC2gPcdlRzMa53xo4LxNBv6m3Po0N13kaU/Bo85nS79BUXlDhzAPZSzNkDBYsZE/jzpHdIlyDwsXQcMJDrevxrNvnMgW1JziCn1Dvuz8bu6vcROdoIRKoOAD/zsnwcMDU13Tk4qtv3K/vPO5/ANN1K0YAHla9ZQtmw5uS+9zN7fnE3m/ffjDlNqX4fDwfXXX0+7du2YP38+c+fO5csvv+Sll1pO9udFj3xDXqX/h1Zzl4LmadjVlJG+9wQI1Pagr6zv63DgsnhHxy0qOBaSIIR1sbfCzsYAX4DLcPADDvLL7Q1XbqFUqc1WzprCpLS686ZEREbRqXfvBo+XUubi7FtVYtmEaDUgKAPuoJy/+4lj+xE2XqPSe6cG+R/v8hsrLBBWfvK+X5uKwoTbFEdp5VdorhqnjL0bjlN4vHUODk6UYGwqh4DhQG33hpFAQKuYhBBpKG+x04FS4G1UNkmnEMIKzAWm6/16D7hTSmn3aD8b+CtK7bYAuEVK2aITGFRs28bBq69BK6/jBnO7Kfrsfzizsunx8kuYIk7MW6U22dnZDB06lDlz5hAfH0+fPn0455xzWLt2bUjP01jy9x/nUEHdxtTasxSLqR0RJndg9pQq9JlKjKbhiCkAhwn02YPLVUlJXg6JHUMbHbqKIRYrIwN4zL7Bzr+pxA3ENjJeVWsi78gh5MrldZabrH2JjBzKOOcCrPozkZYST0piFNnFagC22c/6mVew4QQK0apX9gPgVoIFE8QM7uDTTtM0vw7Le9auYt0Xnzb4fRwWN5aSz7G2uwqTyYSmwaYfDjH5ioENtj3ZCGam8iLwXyHEbUKIcfrnduAl4OWGGgshIoDvUGHzRwKXA1cCD+hVngDOBS4ELtb/PuHR/mbgVmAGMBkYDHiH3W1haE4nR2+/o26B4kHZihXkv9twNONg6d69O//5z3+Ij1cL/7Zv384PP/zA2LFjG2jZNGx+v/5MeW6X9zoPLaI7mcVpgdlTqkjqCXFq1GyOP4rJ4v1SyQqTCkxzubnLHY3V43VV4UcVdjWlPEklDqBDXCR9O9af2+RkYPlH76JpdXvGRcZPI8EeQezgU6v3WS1mLh8TWIj+BTj4d+1kY27I/2gXOW//6lP/+IubKVuX5RPw85cv/xfQ+QD+n73zDpOiyvrwW10dJufIRGKRc0YWARUjKoqoaw5rWl0/dVXMWXd1dc2scY0rKiyiwJJBQHKOBQPMDExicujcXfX90ZN6UncNMzDgvM8zD3TVvXVrerrr3HvPOb/jVotRXHWlrw/8loe5vH12IDoyfhsVWZbfAd4EZgLrqn8eAp6VZflvflwiCdgM3CXL8kFZllfhcfZPlCQpALgXeFiW5fWyLK8G7gfuliSpZrrxMB6fzmJZlrcANwNXSZJ0agtBaKBq9Wqcx475blhNyTffoLpbn6zli0suuYRp06YRERHBbbfd1m7jaCH/eMt5HA0jv3RiPMctAyG6u/+DCELtaiU8IgudmOB1+tjeff5fSwOVq44Tb/N+cDZ60AFZ9XIyZoxI8Vm18UwnR97P4S0bfLYLMecS0Nd7Z/3WcV1Jj/avouo8nMyPa7BKVMGR0TjL3pVvoXTuIYq/3Ivq9HwHi45lkZfhf9VHANW6vfb/iltl5zL/v/9nC5o+vbIsvwwk4ylwEQ6MkGX5PT/7ZsqyPEOW5QoASZKGAlcCK4DBQDDwa70uq6uPDZYkKQHoVv+8LMu78ax6fBc5OE2Uz/9ZU3tXbh6WLe1XPOrvf/87n3/+OTabjfvvv7/dxtGCw9l8BUBVVRtFfun08Zww1SVG+k21XyU9wIxR8X4o5exuPHM9WZwFZipWeGfsr8PJ8hb8K3GhJm4d1/4lc08nqqqy5tvPvY65jY3zVgBspiiKYr1DfcMDDXx1+yi6xzbdpyF/P1HCsmT/o+lsciklczwr15J6Ic/+ord7G5E9v+ZgM2urcnmmo0WmpQsep/xaWZafqD6WKUnSDuBaWZb99oJJkrQXz/bVVuANYApglmW5dgohy3KFJEkWPEasxq+S0+BSedXnNeN2u5HlxrMQm81GaGgoNputiV7acOQ0vF3fWLKzEAcN9N2wFXTv7pndP//889xwww3s2bOHHj18C+C53W4qKyvb5D1piKKWNn9SrQS1/sxeQBBjqQx0Nvm3a4lANYFUoJfTwaEGjvni/GwO7N+P0FZJh4pKwMJSxHpbKVWovNHQgVyPqECRFybFUZKbyakV5T+1FBzYS84B75WhST8Zt2t1bWkDQRcO6CiL7MWcn08wKGAZ3WK9ZWvenBLPErkcNns/sAcnBHC0wkmxpW7F/9zxQnoHhpHcfJkYL6w7CjmU5iInT/v3V++sQnVZcVeLxTrtblbO2UG3UdqVkjsibj92UrR8iz4ALMBH9Y4NBex4nO9auBE4H0+J4rnV/za1+WgHTNXnaaJNzfmOiV5TbikAQiv6tERBQQHLli3zOlZjSEpLW3ignyKKE5uXtWjopBfEGIxOG1WjtGcr26L6oAo6urjcuMRKqJeVrShOzMVtJ9mi329FLPRekXyAjUJUDE0ssKb1DeeDy1PoGtVxP8ptgaoo7F+6wOuYoE9CNHZHHzQZdGGgC0MfNLk2FDnUHse2/+Zjc3kb5ACDjot6hzeq3/Lc+V148+JkooPq/r5BQLRVW4Sf/oCV4CjtOrkOo4PknF+9jh3bbuZEhpW1n+Sz9pN8ijPbfnLWkdDyBDsXGCXLcmbNAVmWsyRJegRonLHWArIsbwOQJOkWYCMe/0xT3ygTHkNmrfe6sonzmhFFEUmSGh3PyvLElwcENM6X0EpQ377YdzRdoa45QgcOxNQGY9eQm5vLI488wqpVq0hI8PgSdu3ahSAI9OnTx6/fUxRFIiIiSEvzL69AC4FTJQI+zMEWlNToXEMnvU6Mx+lay7kTbkGKbvy388mavlCwByUwB8Ed51V0KVBxNfl5aImmsrJdxVYKtm/zcsdvxcV8nIQG6Pnp3jHkvLndq1bJi9edg8lw9kd87Vm5lKpC74mCIXA8giAgGtIRw+9osl+EuQt7D8lcf8U1XscdLoUbyPKq3/K1JGHU6/g2OY3ps36jwuZCQtQsRhlYpmPEhIkcWDSPwswjfvcrSy4jZflKjiVPRBE9yghOq8LBFZXYzJ5Z/uG1FsZcMPC06ru1lh07dvhcrWhZqViBpirURIMPbWxAkqRkSZKmNThcs5ltB4IlSQqt1z4MzyQjB6jZ3GxYAi+RxltiHYaIGdf4blSPwOHDMHXX4ID2g+HDh9O7d28effRRDh48yIYNG3jqqae45ppriIk5/RULruh/DTsSvkTvbDw3aOikD3AJ7Bi5nr5RrSxcVVMJMvgYOr23sz4vQ1ut9aayshVFoXTuIdR6UjM2VP5WPSd6/epBJEeF+F2J8WzC6bCz7gfvNDedoXuzRa8acnRj0wEdzUn0SwmhfH7rCAIM2uXywaNuLAgCwy+90u8+0SEwKiGfE2GVJOZ71+qp71epKLSitJBseaajxah8B3wsSdKlkiQlSJIUXy3d8hGeKC5fSMCPkiTV94GMwJMw8B88OU3j652bUH1spyzL+cCR+uerdcgigPavtNRKAiSJkEn+6yfF3HV3m9+DwWBg1qxZhIeHc/311/Pggw8yYcIEnnrqqTYfqzUkhyYTNnUkB8Lfwmir245rykm/ovdyrh18YesfwtXikjHhx9DpvPNScg8c0HatJrKyzZvysR/2jiz6GDu5qNwyNp0L+ydgEAXyo0y1D8KCaFOrFYDPJHYsXkBVcVG9IwL6wHP87h9UkeC7UQOGpUXx4R+HUSG0Xt24zznnMsgPSRnRYGDqzdOZZLPy22BIPbYcoZmCXsBZnRipZftrJhCFxwdSs1ZX8OSKPOJH/1+BncCXkiQ9AMTiMUgfVW+jfQy8J0nSzXhEZd8F3pdlueab+w7wgiRJWUA+8DHwgyzL7V8U4yTo8rfXyL7tdmy7d7fYLv6JmYSM9/9LpoWEhATefffddrl2W/D06Ke5z3wftu/2osPzHqhKOah1LjS3oDIlJI/Jg//U+oGqw4q7Gy2UuETqu3iLjmfidjkR9a1PPi1feNTr9V5c/ICD/klhzLzYkwTX3grAHRFbVRWb/vu91zHR2A+d2DgJsTl0SuNHVY3WWHaJ5wHdlNbYxN5xlF3dj/wfjpCgYQ4d2N+zihcEgcm330tYbDwb532Po5mcM1VR0Pe+AP2mBJKCqmANxJ3YSkH8yCbbf/fCJtL6R3PuHyVCIttuu7sjoCVPxSbL8s14qjyOwpNdHynL8j2yLNe+05Ik3VF/G6tefydwGZ4w4LXA98AC4C/VTR4HlgA/4zFcPwFP1rvEO3iSLP8NLAf2cQbUcRFDQ0n74t9E33kHYnhjifWAgQNJnvUhUTfddBrurmMQoA/gw/M+JFCoU3pVG6xSQgMt3B6YDCEnkfke0wtMYfRwOtEpVSDUufEUt4uibP/0mtxVDipWN5F/4Kjb9nKi8ho2gkx63rtuKCZ9nc/EXymTs4VN83/EZq6qfS3q9egDtSlDu8XG21/+ao1dOSyFfXH+B0G4UFEG1Bk8QRAYefnV3Pnep832Udxuti78GYbdwhW2Ktb0F3CJLY+ZtaeYOX/fSkWxn2FpZwiaQ42q80y2tNDkTTy5J43EcmRZPg5c1cx17cDd1T9NnVfxZN8/3dT5jowuKIi4hx8m5r77MK9bh7OgAMFgILBfPwL6ttI/cLZhU7Ab4gFwOzNxmr1ravQwVkDX805uDJ0OkoYRcmQlLn0eOnc8iqtuoTv7+Zmcf+d99GlBlda8KZ/S+RnganlL5d/YOYrCu9MGkR7jX07F2UDmjq0s+diTunbBnX8mOjWN7Qvne7UZeuElHFmShznY/1onXcw7gMY+Sn8k+lVV5Ru3jXhU+vnxyBOBNb9mcdmVfbyOG0wtryh2rVjMqFdfIebX13Gmjqa4bJDPsapK7Sz+eC9XPzbsrFmxtkfq7tnxzrQDuoAAQidPJur664mcPr3ToNQjZ91+EERUVcVlWU5dapKHhMBKbXpfzVG9BaaajqE2qC7otFlZ+O4b/PTGyxQcaRzqbN6U74n28mFQrKjMxsH1o1K5bJB/juizAVVVWfbZh1QWFVJZVMjyz2bx2/ff4HLW/S0DgkMYMm4S3Y6u8vu6guKi9+HWlyjYl1eBXGzmESxs8UPcU0BA2lSEs9C338MUVDdhcNntbF+7CVW6mMgq/32pJzIryD/cOMv/TOXs1oPo5IzhyBYZVVVwOw7VJsHVJz7QDGltIJ6QPAKHosNhq/CUhm2CjM3r+c/Tj3BoU13tOXeVw7NC8YNABG4PDeWZS39fkwbF7aK8oC4MvKwgjz0rvXOkRl4xHYPNTkzRTuLzfUu1APTM+JGAMr80a5vkRLUAZSXwYDPqxisaTGKCVCj+ah+Krc4I6UQ94fF1AQMR8YkMuWiqV7/t//uF7JgbsLm0TSb2/5bnu9EZQqdR6aRDcOzocRwVn+Oy/NLk+XXlA7CrbaDgnDSMRbkSTkfL1RXdLhcL3nmdgqOeOhnmzQU+Vyj1uVpnwnSWa3jVx2mzsXXBT02cqXvPQqJjGHzhpQiBnqyRmOKW5XF0bju9D3xNcu4adIGBLbZtiYZ/h6bUjV/Axr8b5Fa7TlgpmS2jKp7fQRAEzrvtHsJi4wiLjWPybXcz9OKpXttidouZ3Xu110g6m6LBfj+f+k46LAVHMiiuWNvkCqWGI8V6fnzpKZwnKRVTcKKMjEr/8nPcTmdt1FLptgIfrb0xlDtw5neMB0Xmjq18dN+tfHTfrWTuaHttucriIr558iHWfPvvFtuNnHo1BqMJY0oKYlwc2annN9u2x6EfGbf+SbpU53sEDh/e6vvrkxiGUfT9qPsUO2vxln2x7S+hYlldAEdCUDcuTb6bS5PvJiGoG4EhoQy64GKvPke3L0VVtel9nSXuFKDTqHRymlEVhZ/f+hv4sdedf/gQ6+d+d1Lj7Wqm1nhzHNq8HnNZKdYy7cbMWnr65Tia8nO0ZVEyp93GnFeeofi478j+Q5vWoShuBL0e69hJVIY2r9CQnPsrBlddVFTkdde1+h4jg41cPMB3nosKvICVow1WMpUrjmHZXdhsGeJhl1yBWE9eyWGtxG3fq+keQwyn/7PSVrSHUTl7U0U7aXMyd22n/IT/+8m7ly3C6Wh9jYq8wxoz5xWFgqMZVCnN1/5ojqyKtg0Vbc2KIy/jYCM/h9vVdqq5u1cs9cugABzbu5uj27eAorDF4f2Q17nrfBqB1kKvxMHgsWMIHqstBLkh95zbo3YbzAWNNMNqpjQW4AmsuBqItJV+fxBHTlWTZYhDIqPoP9F71aVYN6C2kPzYkPCspb4bnSG0h1GxA9q/gZ38LjmwdpWm9jazmayd2303bAa3Q3upXrfDyX6dto+0BZWK0LYTB3W7XCz+1zu1K45ln37Y4oojP+Mg3z79CP956uFG57558mGy9+w66XtSVZWdSxdq6rNjyULyl/+EzdLT63h61iICbMUE2IrpdXB2bQhp4NChJL399kkrSEsJoXx4w9Baw9JQKqc+x1CY6TKj1rMrqlOh6NPGCcylP2XgzDcz/LKrvO5RwYLi8E+lIbwsA3vGKu2/VAelxU+9JEl+h6/Isryv+t+zP5urlZjL7GRsO4G51I5o0BGbGkr6gGh0fuz3thVvvvkmv/zyCytWrDhlY7ZE1XFtEvYAlSdaL/cWHBmluU5GcGQUG8IKmVjsf58lODk3ovXO5RocVgtbF/7EzqWLMJfWieKXn8hn+eezGH3FNYREeWemZ+3ewby/veAVylufoqyjzHnlaS75y6P0GtX6iDpLeRklOdqKUB3bu4uVJRFAXQ5HaGU2adlLSM9eUnvM0K0bUddfT8Q109EZWw6q8JdJveP5773jeHf5IRbtzWc6dQmZ4QF6Kuwuauz0etXFxzoHf1LrxlatjVcels0FWLYUEHZBGr3HTmD/2pV1J6tWoxr7IAgtf79Tjq/AGn72JED6mkrtwbOd1ZwbqeacSn0t8U68sFQ4WPv9QTK2FdZGktQQHGFi+EVp9PtDUrsnP+3Zs4dPP/2U+Pj4dh1HCzpLke9GDRBLWl/+t/fYP3Bsr/+z9JCoWBJ69KT7QFizMpfx+I5Aq0RleajAPYknV0PDXFbKjy8/TVF2ZpPndy5ewKEN67jqiReIS/eoEVjKy/j5zVebNSg1KG43i979B3Fp3YhIaKjT2jiJMX3wsEZtHFbtgQhup5Piiv5ejum07CWNHjDd/jsXnantSwH07RLG29cNYdFT3r619TMn8/OuXB6bU7ca+VKx0V8UGev28WhToWJxFkPHXeBlVJw6GynHvqY04QpcxuY/C0fTL8Gk69CV0TXha4rcFU/Fxa7N/HSr928nTVBVamfO37dwaMuJRgYFPKuX1f85yG9z/MuBaC0Oh4OZM2cyZMiQdh1HK6GtMKQJEa2fv0QlDfaSZ/GFSS+h04lcNzqNhfj2RVSi8hgWLhiXhqhr/SRBcbuZ9/qLzRqUGizlZcx97TksFZ7IuV3LF2O3NM7DaAqX08H2xY1DuBVFYfGsuq22Be++Tt6hxitKu1X77FoniAhCvVonlgJiCxuXhzjV2eV6UceMEak8dH4vr+P5bt8BJDW4NpbTe9h4r2PlYg5jNjzbYj9zSBL53c71e5yOTosrFVmWfYohSZJkBIYB/gkn/Y5QVZUln+yhosh3ZMeOZceITQul1wjtaqz+8P7775OamsqYMWP47LPP2mWM1iAqiXg+Ov7FdyQEVBCX1Pr3aNf83RiCLsRpnu9zTJ0+mSr7YMzldhJCA3g8NAwqm3/I/ISDb7ATnRTGLWPTW32PAIe3bCTfTzl+c2kJq774mPRBQ9m64L+axtm7ehkTbrgNneh50B/fv4cV//6IqtK6vT5bVRXfPvUw8d16MvGWPxGZ2IWNc2ezY4k2fwoABu9Ko6nZSxFQ0YWGolR6lJ0MqalgaIOcpFZw/6QeFFTY+GZjNoHABWjYenOpDO5+Pge2rqk9VBFkoiS48e8SXbSb4pgBta8DCkdjqXAQFNY2W32nEy3lhMcAs/CUAW64wlG1XOv3Qv6RCvI0yC9sX5JNz+HxbT5L27t3L99//z3z589n8eLFbXrtk6XY0RXRGILb4V+d+NExxyClaeVXf8g/XIJo7A5MxWlZDGrzBl8fOAlBZ+T4xgMkxyQQ3oJBAXgLG0PTo5h14zACjSe3G7xzmbbQ5/1rV7FfY9ADgN1spuhYFnHp3Ti8dSPz//EqSjOz84Ijh5j93GOIBgMue+si8PSmupWy0V5GQsFmMBiIf+YZit56C4CEp59u15VKS+rGgiDwwuX9Kay0U7aviBCNqlOGIpHUtDiys+oUAI7EhRNgLcQW6HE3B1oL6ZnxA6VRvVF0HoOjuE2sn3eYyTf1afK6ZxJaDME/gULgWuALPArBKXiUhJsu2fY7Z/86bZm1RceqKDpWRWyq/0J7vnA4HDz++OM8+uijxMZ2vBiKKmcC+qABqEoliqvlxe658Yfp3r8vxLai6mM1ilMBE4jG7ugMd+Ky78dtXUVTeTJux150+gnkHNpH2Fbvh+gGnIxu4F/54PohTO6feFLbXjXkyvtP+hr+8tVjDxCTmk5xzjFUH1X9VEVptUERTX29inKlHluOTnURPnUaEZddSsRll7bqulrxVX5A1Am8c90Q/vH2eijSliGhWl2MGjeQ7Kw6eZrSkEBSc7+hPNoTuJFWYCfIVkxq9hIy0y+pbXfgtzz6ndOFhG6N1czPJLSEHQ0EHpJleQ6wHSiQZfnveKTrH2yPmzvTKc33b2+7PiV52vu0xAcffEB8fDxXXul/BbtThb3KitUQhyDoMYRcgaCLbLJdUmA501L2MCy6ACbOPKkx9a66laMgGDAEDMQQMtVTH72Br8Xt2IuqOgkzG3CX16vtgsoH2BvlOkzoE98mBgXA1YrQ55OhKDvTp0FpiqDwCM696U66DW159ZgQGoY+8ILa13qnmS556wCIvu02zeOeLL7KDwQYRO5q4F/xB8GkJ2XUeSQGeEv1H49woapmVNXMsXArxyMhLXspAVbvQJVfvzuI0oTv9UxCi1FxATXv1EFgcPX/VwL92vKmzhbaMHG51cyfP5+NGzcyZMgQhgwZwmuvvUZubi5Dhgxhy5aWKhi0P8fW7IZ6TltVaVQtAYDpabvpGlYJV3wI6SdXyExUGucaiIZ0AsLvwBR2O16Ld9WGybKDuArvh84inBxB4UODozbX4etQFWMban0FRURo7pM6YDCxaV3b7B58Mfqqa7n97Y8YdsnlXPHo00yb+VyjNn3GT+SaaSOpMl7rFVqbnLMavdtOyKRJbV5Cu62I6hWFQ+McwdIlCCGhPyMlb5l8pV4Oi8Vk4P1LBFSc9Dw8x6tdYXYl+9Zq1w7rSGj5FmwE7pUkSYengmNNjc3+NNQp7wSA8FjteQqt6dMSX331Fb/88gvz5s1j3rx53HXXXcTFxTFv3jz69+/fpmNpJWNzXXKY6s6nqS2oCIMVXZ9L4fYlMGjGSY/pGKfD4Kxq8pygC0A0eu9p9wgJQOeq+5rYUPkEOzoBLruiNw9GuHkwws306f3a1A/Qa7S2/JGUvgOY/tRLXPn4s+j9DcUVBMJiW1/0bPil0zAGBlVfSiC1f+P6IVNuuYXiHcdwKSG1x3RuO8k5qwCIvuP2Vo/f3hS5XCxR/X+0uVCZ4/KsaLtPe4gYU/O7DmMPJ/DTyDCii3YRVewt6bLhp8PYqtpO9eBUo8WozARuBR4CvgL6SpJ0BE8Fx/+0w72d8fQe2zj+vyUiE4KI73pyuQ0NSUpKIi0trfYnMjISvV5PWloaAQGnt4xpcU7dlpLi9Jb60Atuwgw2JidkIFz9GSQ1zpNoDeOn3khszpfN1g8XTYNr/x+sj6BbmPeDcjYOilCZ1Dueq4altFsFx34TtBUkGzzFszcfGhXDJff/tTaaq1kEgSl3PcCd733G9S+/2cq79F6KNyUNr274mO3lF3i165K3DqPTTOCQIQQNHdrKsdufncfK+Rw7pX4KhMi4WZPv2V4Vel9Iap/mc8dFSxCB1ljWSXH0yPgRQambUNnNLjbMP3JyN38a0VJOeDOQDnwhy3IpnjDiN4DbZFn+S0t9f68kS5HEpIT4bljNoMkpZ031N3+wOKNq/+92eWdmj4/L5M4em0kPKWvTMXtlb2L/OdvpdnAWBkfj7TadPhZBnwTAwMg/INbbnitF4ZtqefQbxzQvhniyqIrC5p9+9Lu9NGY8PetlxvcYMZqrnniBqC5JTbYPjY7m8oefrNWriu/WnYBg/z+nAIFh4bWrlBoEQeC8i0YTZnQRZnQxefJADq7chUWpV5pXcZN6zKPm0JFXKQBWp5um2fsgAAAgAElEQVQCVP4PC0V+GJZ+6Ole5Zms5GXI7NjtW7mhMiCUo9FuUo8t9zq+d00OJ7Ial1A+E/DbqEiStAIwyLJcCCDLcr4syx8AKyRJans97bMAQRCYcmd/Av2IPe89JoG+57R/lcAbbrihQ0i0VGSfwGH0OOZV1Ynq8haVTAlqW2NSy4FfeMhdzIopOwnJf4be+7/0EjME0JsGEWVKJDXEeyvsM+xY8ISgju/hn3x+a/jth2+Q16/x3RAYEF3CRVdMaDQZSSWDWxKWcVXKboy6ullwsGjn9qQV9BDqost0OpG+EyZrusf+557XeALkcpC+52/c2X09d3ZfT+rOF9ledqFXk/gTmwmwl2Ls2pWQiRM1jXmqiQnxfG8zULgJMx/ROPzc3mC1dkeFgLvKwfofvkXxM/AhOzqchJylmGyldQdVj9M+a08RXzyxji+eWEf2Xg06QacRX9pf5+LJSwGYAPxJkqSGG9J9gI7paesARMQFcfWjw1j59QGOHyhtdN4YIDL4/FSGX5T+u1qlZKzcBtWJZYorD+rJjQeKDmJM1RIgkV1BbMNEOHMRAarKK7ZC5ky28q1zPdcuqiC763U49cG49QHoDD0ZFBbl1a3AbWG+6Hk43zAqDV0bRXk1ZO/q5WyYO9vrWIjeTlygniOVemq2nERBx4zUnSQGlcHs6+De9RBavfW07UuYfz8CkB4ClyXtZ2m+R8Dx/IRDiM4K+OVBsJXDOZ7AzSFTLmXnkgW4Xb4zyPUGI4PO964hwu4fYfGTZJd0YWX5iwBIgasocyd7NUur1veKvv22kxaJbG+Gp0URE2KiqMpOBSrf4uBPeG8ZP4WF16krKRzqhhPf7Obozm1+jyMgsCM9gB6H57K3X93qreBoBUs/3kVNBPfKz3dy0+sTO/xzwleeSjHwCB59LwH4M3gVG1CBKqCxFGontYTFBHL5g0MoyTVzaEsBVWV2RFEgLi2MHsPjMAb8/vJGs/ZkA57sasXl7U9JCSpHCOsCOj1c8kbbVjAyeh4AemBGZRXTqeKB8TqmL30GRUxl38DHSDToiQvw3jraVboaJXoMJoOeq4clN3Hhk+fYvt0s+de7Xsf0gooYPJ1cXQ8MIZk4LZ78B13QefxccSej1W8YoC5C2PgvOO9ZKDkCv/wfAG5V5Kh9JHsd5+MO6YuASq6yiGT1P+gFJyx7FrpNgC5DiEhIZMq9/8eid/+Bqja/1SPodFx430OEx9XTj9v0MSx8BIdiZGnZa9hUT57FNvPVXn1jCncQbClAjI0hbKp3Gd6OiFGv4/pRqbyzvHmtuc24mY2dGdQFR7iPWugRMoSMSv8NS0ZCIEMytxFZeg6lkXV5WPVTgqqqYNGs3Qw+L5UuPbVHB54qfMm07KZa10uSpJXAtGp/SquQJCkZeAuYiCfUZwHwsCzLZZIkhQHvA5cBNuAD4EVZltXqvnrgH8D11ff9FfCILMtnTORZVJdgRk3tlEkDqCjRU5M7qDi9/SmpMSI83E7Jf2njIK9Oa0oH3BqQgv78e0GF1PxieoR6C24W2o5TUrmLtKAkhg8/h8jgtpfSKMnNYf4bL3tlswuo6IKvxK7zfGZEQzpieF2esRNYU/knbEoYIzd8CIZAOPorKC6O2Ebxa8WdmBVvBePtlivZZ5nEOeFf0DtwJWz8CK78EIA+4yYQEBTM8s9nedVgqSEyMYlJt95F+qB6zvW8XbDoUfZazue3ihtxUJe4qzbYXU/L9tQMibrppjZTHm5v7p7QjRUHCtiTU1FbhyWp+veqqcPyL+wMQ0+Pepq6g6MmUmjLptzpn2BqIPDlZB03rv6ejSOe8Aq1r8/RnUUc3VnE8IvTGXlZ1w65atHiqJ8oy3KpJEmTJUl6QJKkByVJmlL9sPeJJEki8BMQgseoTMWT6/JFdZNP8Exdz8WTrf8gcF+9S7yCJ4x5KnBF9b+v+Hv/nXQcFLeCVfA8uFXVXh1OXEdK/4HtN/jwW71eqip0Md9BtCuaaHc0faMiCBW9v6g7SzzKswMr9nDj6LZ30FsrK/jv357DZvbeWTYGTURn8D0J2Wy+llxLOqx8GTLXIFsnsKjs0UYGpQY74Swvf4Cd5kth71xw1U2HuyYFc8vwxvPGaSl7uHVkOeldgr1PbJzFtsrLWVVxr5dBaYSqYg2MRRdgIHLGyYeGnyqCjHq+vn0UY7p53sum6rA4gOewevlXRJ2e0XFTEQX/diG6q1Z+HQh7Uwx+yeBtWZjJrhXaSjicKrRof8XjMQpDgUw822FpwAFJks6TZflEC90BhlT3TZRlOb/6mg8AayVJSgOuBgZVr452SJL0LPB/wHuSJAUA9wLXybK8vrrv/cB/JEl6Wpbls6cYwe+Agq0Hces9+TiKK4f636IQvZ3IgdqcxpqI6QlDb4ZtnrmMW43GrdaFfptE7z3zY+YDFNs9yWhp1mOkGixA67Yeygry2bl0IfvXrsJcVoogCCT26oPTYqYs3ztQITk0mCK9/+G2O82X0sW4nwpXLCvK78Of+eLaylvpYtxDbO4OSB0FWevhm+mI9krCDcMpd3r+RhEGK+nBpQgHF0HWOrhhLqSMAKeNgm07WF/1ku8bFAQO9P4j6RWHEcPaNmy+vYkIMvLtnaNYl1HEDZ9u8qrD0jUmiKNFFjJReBcbj1CXZxZhjGVg5AS2lyxv6rJeDAs5wc0VDrLTpxJl9083bsPcg/QZl9jhts+13M07eLasusqynAMgSVIX4FvgTeAGH/2PAhfVGJRqap4mY4DyaoNSw2rgHUmSEvEYr2Dg1wbng/GsdtZr+D06Oc0cWLsd8KxUGm19BZchdJvQvjdw8Ru4K+2U7+2CRRnfbDNFVdldttPr2M4lCzn3Jm1Sd6qqsmneD6yb/bWXv0JVVXIPNK5l3mPEaMqPdNdUP/WIbQz/K/0r5e54FD9qvnjQsdtyCZM+uwBiJCjLApcNQYDzEjJqnfuTEzLq3Fr2Cvh2Opz/Ehxbz86K85u/fAMUnYHcuMF0dbtA7FgPQl8IgsDIro1Xft/eOZqp762jsNLOPJyMQu9Vc6dX+HDyrUdRURkeMwWALUWLybce9bpOhMHK9UWh/GD3uy4iLrfAgTXZDDy/Y22pa/nLXghMrDEoALIs50qS9DDgs8CyLMvFwP8aHP4/IANIAhqW86uZuiVXnzfLslwr3CTLcoUkSZbq85pxu93IcuMaETabjdDQUGw233L1vxfcbjeVlZVt9p7kHCyi1qg0cNInRhuRc0qBVrvufCKY3QQcvQmdj7rzpW4Vq9gVz8Lcw67li4kbMgpRg0/g0OplyMv9Ux0OS0yix5SprH6voPnSeE0hCBy2j9XQofrerOOZEPYvxCLv70J6SBl39tjcdCdrKcy/D5dq5LDta23juSYQc/Ag6M68mn6qqpIYqievWq06MdRAeV4WD4+NZubiXFTgb9jog0hMvZXiyFhPpFyA6Nk6HBV7KYtzPsPmrsu4n5s7hKHh2ouSyUt3YUo9ddn3bj/CpLXE9NloerevVVUfJUl6DLgKj+8kCGgofVrz2tTM+Zo2bV8erpN2xW7zbB+pihXVXeh1Lrp76xWI/UJVMa0oR1flexkQrdeRGDwA6s08nTYrObu3+z2cuaQIeUXDuVTzdOk/GL3RhNBCBFZb4sKERWmsilvhimOv5Xy2ma9gr+V8KtyNFQPM7kgNq6LqPkoMiqbHTsdBEAT+PCaW+BA98SF6/jwmBkEQGNIliGsHenKuylB5qUHN+wAxuNageF4HcVnKPYyOvQyTzrNdZnPC5mInilvbZMpV1rTk0OlEy0plCfCmJEnXyrJcALV+ljerz/mNJElPAy8Af5FleYEkSX1obBxqXlsAaxPna9por2kKiKKIJDV+gGVleeTXT7eESUdCFEUiIiJISzt5J7W9wswyk2d1ori8HY0RBisp51wFTfxd2gpbRilFRYW+G1bTM8BErrEPbkddCeL8nVs577ob/Yq8Wf31Ok3KokXyXi4eGcPGqkoqw9L97ncyFDvTCBWLq/+fyvqqG8myD8V7zqmQbtrCmNCviNIfR1WhyNWa+1PpLUkI7ZTn095IEvxxUuPjL/ZQOFS+gS1ZpWzBzXfYubaF+a5OEEkL6UuUKYEVed9ic5txqgpU/oAx9Bp0on9+O6Nqa/I51l7s2LHD52pFi1H5K7ACyJIkqabwRRqwC3jA34tIkvTP6vb3yrL8YfXh40BDoaya17l4suSCJUkKlWW5svo6YXhWMA23zTosiuIm76BMZUkRosFAfNfuhMW0XtDPX7Zt28Z1113ndSwoKIjt2/2fcbcVR1dtqw2XbJSfElzuCfltR8ybCzS1jzXoCAsaRmk9o3Ii8zB5hw7QpZfvgkoZm7S5+4qyMymbPZfokhmajEpU8T5iindxNP0SnEZt9XgWlD1NomE/KaZtbKuahoumRE11ZNpHkmPvx9DgeWQ6hlPg1P4wMwcWnrEGpSX0oo63rxvCxW+vodzq5KifDrFQQxRjYqeyMr9aPlGtwlH1A6aQGQii74AGg+pfddBTiRaj8i2erPqReKTurcB+PEZlER4tsBaRJOkF4H7gZlmWv6p36jcgSpKkvrIs76s+NgE4IstyviRJ5YAZGA8srHfejEcxuUPjdjnZtuhndiz+hYrCekFygkDXwcMYdeUMkqT2q/h2+PBhevXq5VVGWHeaspkztspUpz41ctKnJEVAYPsmdTlbUeMmzBBFmT4J1VU3f9mxeIFfRqWmdrwW8m1JHEs51+/2OreDXhnfE2QtRBGNZHSfpnnMPGcf8py+fx8nwWw0/1Hz9WsQKlfjVqYjnoE+FV8kRQTy96sHctdXW5mhoQxxXGAqUcYEShzVMUxKJfaqH9CbRuK270JVqp8ZunD0piGIpr4IggnRZeFYembb/yIniVaZllvxZNDXbOT1Ai7HD5kWSZKG4KkS+QawVJKk+oXGc4F5wJeSJN2FZ5XyfHV7ZFm2SpL0MZ7w4pvxuDDfBd6XZblDe9SdDjvz/v4i2bt3ND6pqhzdvoXMndu48J4H6fuHJtbVbcChQ4fo2bNnh6j8WJbrAhFUpQpVKfE6lzp4VPvfQCtq3AgC6E2DcdYzKgc3rOXcm+4gKLxlI2gICMBh1bZD+2vFvbhF/1YbguKk/75PEZ2eLb3EvN/ISjlf82rlVGC0l9Fv/4bTfRvtypR+CTzSP4lue5quDdQcg7qdx8oD9YIelHJc1gbxT0oZLutKXLbfMARfjCCmcDS9Y0V+gW9HfY1My1+pk2n5a72fR/AYG39kWq6qHu9RPJFd9X96A7cBh/GEDX8MvFlvewzgcTy+m5+BuXhyZp70Y9zTytKP3mvaoNRDVRT+9+E/Ob7fvzrtWsnIyKBbt47x4bO6PUKMSgNV4mijmeB+7ZifUo0+SruvzOJW0Rl6gFDnbHW7XOxe0bIrUVUUgsK0rbwEIQCnzjug0WQrgSak+sNLZYbu+CcG6x7+fI+Oe+7RgWJl4J5ZiK6WU7cEt4O0zIWElZ+cxHp4WQbpmQsR3C0LW+idZgbtnkV8mQ3dGV7Z0Bc39Iz33agBSYm9Ce6V6l9j1Y6z6idc7hzSNo6nsqRjzatPmUyLLMtPAU/5aNZsqq0sy3bg7uqfM4KS3OPsX7PSr7aqorBh7myufrLtC2cdOnSIoKAgpk6dSllZGSNGjODxxx8/5SuX8qO5OIweocZGW18hlZAyut3vIWhYHLYDJb4bVlNhL6dCCUIQRETTANy2upn2zmWLGHH5Veia2Moxl5Xyvw/eojBL20NbZxqIUE+iIyFvPX3kb3AYw8hKmUx+guc96n5kHkl5v1ERCK/MECkP8fgpNksqY/dnMnzbG2R0v4LiqH4geM8dI0plehyZR1hlNmQuoDiyDzsH/VnTfQIM3v5Poso9ulgxxbvJ6HYFZZEN/CyqQkzRLnocmUeQtRBVADq4kOTJYhC1+4wEBGb88XLee+Utguz+eCUUnJYlmPS3s+Dd7Vz1+EgMpo6xpei3T0WW5Y6tU90B2bV8sab2Wbu2U5afR0SCtuJeLVFZWcmJEydwuVy89NJLWK1W3nrrLe644w5+/PFHDIY2VAD2wf7lmwCP87HhSiU1LR6MQU30alsC+0YjRppwlzYVod6YDGERnkU26E0DcNs2UrOHVllUyPu3X09AcAhJUh8GnX8xXaQ+HN2xhcUfvo2lXKN8vxCM3jSk9mVSzq/0OvQ9WXEqkRXl9Do8l16H59aeXzYI5o4TKQoXSAxO5E8D/8TW8i8Zu/8QwZZ8Bu2ehTUgmuzkSRTEjwTUWmNUn9Aq77+Fv4Sa66L3wiqzGbrzHXISxnC4+5WAQEL+RlKPLyPAXvc+6Lt36/DqxCeLPlp79VZHuZ3g7KMEOrzfm/SQfgyK8myL7yv9jUOV9aqMKJUoziMU5/Vg6ad7uOjugR0iCOLMSms9w8jP0B6ZkX/kUJsaldDQULZu3UpgYCBidTXA9957j/Hjx7N582bGjtWeMNdaju/PBcJQ3OWoSn0HtkrykFNzH4KoI+yCdEpnN058bYi5dwRJxhOU/nKQqrBeCLpQBDEW1V0XbOGwmHFYzFQUFrB/7SrCYuO8gzH8vrFgjCHTEHSeLbaUY8vpcXguKwYJfHSRiOhSeW+WQlS1N7MgHD66SKxVcL5n0D1c2fNKekX2YsXaa5m0y2P4Am3FSBk/IGX80GjIwwlQHgwDj1gQXTbcev+3BvUuC3pX422XpPz1JOU3H/EWc821fo9xppIXIpKHmxQt6XuldkpW9aJX6HAyKrYTG5BCn4gxJASm1zYZGnMePcKGcKhiK4crd6Ci4nYeQjT24OiuYjbMP8KYK05/FZKze8pwmnE7tQsou51tnx0bEhJSa1AAYmJiiIiIID+/sRJte1JVWlM/xXtmHBdQRWCf9vengCcrunRty0J8FlQ+xcbSFBNDp7xGVcA6AFz2nV4GpSmaMihGfQiG0BvRB00GIarBWQGdaTimsBvQ6T3bkWlZi+hxeC7Lhgh8dJEOVRBwGXR8eImOE+FwIhw+uVBXa1BGJYzisu6XATAwdiDmB29k2eCWZ6zrewv879Hx5D13O3+7N4r4E1tabN+QhPxNOPqmE3nTjeCnuoAYG0P4lVdoGudMZMfxcr5H+3dfUAwMjT6fy1Lu4dyEa70MSg1hxmiGxVzAmLjLEdCBUhcEsu1/WcgbT+13uik6VyrtSHBkNNB8LYam+zR86JwcO3bs4NZbb2XBggV06eKpLJmbm0tpaSndu5+6WY3icmPTJVb/v8HWV4ilzWrQ+8K87QTkeIcV21AJqNZEKUVhBlWejNqlh+iXPIKoEVWUbSrCZVmlebxesQaynLehE/Sgj0U0DsTt2IvLuhYQMASdj2isC6IIL8ug+9FfWDxU4NML6gwHwM5uOv58r/c8cHzSeF6f8Dp6Xd1X+ZExj/FPo4mZSz9jylY34/eCWO0btxrgtek6+k6+mrfGPIVBZ+BE92s5+u+byU0c28j/0hSC6iYx91fSf51DREg0IePGcfz+B1AdzT9IdWFhpHzwIWJox4tKa2tsTjfzcNIPkQt9hBa7UREb6PEE6n2/RynBEtaoiews9y4RseKLfYRGmTiwfil7ls0BoNeYi5l82/UYTKdmq7tzpdKO9B7bvFhhUwRHRJLSt20d9X379iUuLo4nnniCAwcOsGvXLh588EFGjhzJoEGD2nSslsjZtAe3PhBVVVGcDZIeuyW3bXXHZlDsLooWeDvOt+PiCSy1cuYvYvWSaPjX6sNMmf4ainUp3vXpWkbQ6Zj2+HPojWMQ6smfC4KA3tSfgIi7CYi4y8ugAJiDE1k0zFBrUK7qeRXfXvwtV/a4El29B36gPpBZ583i/cnvE2zwlqPXCToeGv4Qb937M+V/vZnXZxhqVzgfTA/ihfvm8Ny45zHoPO95VEQC2fEF9MyY49fv1vPQDxzpUkxYsEeaJGTCBNK+/orA4cObbB8ycSLp331H4IC2D0LpiMSFmVCBV7DxGXbMzcSxb8TFjVTxOXZcrXCF9AgbgpFynFU/18q7OG0y/3nmIbYv+BKn3YzTbmbvqh9495ab+e/rn+F0tL9OWOdKpR3pOWosIZFRVJX6F2008LyLEPVt+3A1Go188sknvPrqq9x4442oqsqkSZN44okn2nQcX3iUiVNRlVJQ61YKAirJw/5wSu6hcuUx9Ja6IlhuVP6JjcMoXnLm9dlwpIQKBmI35KNlR0NVFIIjo8iz9tR0jy5DMD8NTQAhj78M/Qu3978dQRAYEDuAKelTeGH9CwA8M+YZxiW1rD7QNbwrj496nHXJ43mhf12/3tG9vdrpdXpKLhpF//dXoXdZOdRjGi5DSKPrGZxV9Dz0IwknNpP54ARvIzdwIOlff0Xp7O858eaboCiET72MqFtvw5ic1OhaZzNju8cQEWSgzOLkM+z8BzvfE0Jk9Ry+ApW7MZNdnXX/KXZGXdaTwbvLcByt8HscnSDSNWQA+8s34HZmNPL31UdVKjiyZS6f/mU/t775EqbA9pNM7DQq7YioN3DRnx9hzivPeFX0a4rEXr0ZcflV7XIfKSkpfPDBB+1ybX8pyvQ8tBtufSUEVmKU2ifpsz6uIiuVa7wVfX7CyWE/5DQyTlRhCAjC4dCWjW9Z9wku91jN+wFBahAz//A6F3a90Ov4uKRxLL5aW0Shv/3+cN3DbFm8nuEZG4kr3MaJ2KGURPXBpQ9C77IQVbKPuMJtiIqLjZLAhGseavI6kTOuIXLGNZrv8WwiwCAyY0QK/1rtWRVbgRex8tdq+ZvXsdYalBp2VdoYOyhWk1EBiDLVBPWoqO4T6ASRlODe9A4bSbgxBhCocpaRUbmNo1W7MZfs5/sX3ubGVx89yd+yeTqNSjuT2n8gVz3xPAveeb3ZENPuw0dz0X0PYTCevYLLVks4BDRRPyXcBvED2n38sgVHwF23DVGOwidNCl83RlFVgoLCcVRoMyqGnV8huIZpDpV+ts+djG5gUNqbPjF92fj8X9j0/NuMPOgksWAjiQUbG7Vb31vA8MzD9IrqdUrv70zj/kk9WXOwiH15HiOxCXezq2GA91Zm0K1bAiM1jhNmiCFADMHmriLMEM34+KsIMUR6tQk1RjIkejL9IsbxW+FPFBxZR9HxQmKS2ydPrdOonAJS+w/izvc+4+DGdRxYu4qqkmJ0egMJ3Xsw8LyLiOuAUgttib2sEqspweNPaeik79Gt3ZPhrHIJtv3eW5CfYKfCT82W1OggFKkvZfm5fo9pENzsst2Mwxjpu3E9Qiuz6RvRT1OftuKWYXfx/d8jeH3237j/RysB1dvvKrCpJ6wZFczF0x/nKunq03J/ZxIhJj3f3DGKP/9nG+syiv3q88uRIkaibQISZozispR7KLRlE2lMwCg2HxZuFAMYH381q/Nns+abeVz52J2axvKXTqNyitAbjfQdP5G+439/OaT7l68HQY/qKgS1Tj5EFBQSh7Xv+6G6FMp/9nbOZ+BmPv45LAckhSPFhxJ+7gT2rl7m97iCcQBHHNq39ZJyVlOgS+N0Fdy9pvcMLnniUr5LeoyeH68AFZbN6M6Ay27i3a6XEGRo/wTVs4XIYCNf3z6KrVkl3PzZZswOT6BHgF7H81P7ER1i4s//2YbN6dkKW48LMyrBmqqzeQIz4psIP24KURAZEXMhaw6t0jSGFjqNSiftTua2w4DUaJXSJbACQ6/29adU/ZaLq8hbB+vbUBW3n3p/t52TjiAIJFRtISXQyjGrH9nSgglMYzTfa3TxHkTrRswJ92vu25YEG4K5/Y73oLpq8qkJozg7EQSB4enRfHDDMJ6Y66mW/sq0AUzo5dl6+vK2Udz2781U2V1YgYU4mN7OdQdDDVFECe2nBt4ZUtxJu1NR4NlmalQ/JVKB6B7tNq670kHFcu8xAwfGcOkl/tUBuX5UKlcM9kQuuXfMoUK4HZ3eh+ifYMIYciU6sa6aYqDlBF1yViMozQdrxBVsof/eT1g2RCA8SNuWWScdnwm9Yln3+CTWPT6p1qAAjOwaxTd3jCI80BP1+Ql2DvsRuq7oIDhoHaLQumTH5AA/xStbQadR6aTdsbvjUFUFxemdyZ4q9fJK7mtryv+XiWqv+4IKBh1hF6Xz5frMFvsFG0UeuaAXL1/Rv7a64569cdhNCRhCrkQfOAlB1zBJ1YhoGoQx9AZ0ek+SqaC4SM9cyMgtL9P70PeM3fA0XY/+TIDlBKhuBMVNVPEeRmx5lf77Pycnysm+c9NICzv5CpudnDkMSonguz+NJibEiBn4Cxa20PwEpACFexQz8qQRJATci1K1VvOYJr2Iovifd6WFzu2vTtqVkkOZOExRqK486id6GAQ3CcPbT5rFcawSy1bvKo+h56awMKuELVneQtuDksM5WFCFIMCMESk8coFEsMn7q7GnfDQEgCCI6AMGI5oGoSolqIoZQTAgiDEIgneO0aCd73E4LoPP/igweafAxF0VdM36H12zGtesz4yDV68RuWPAtV75H538PuiTGMbsu8ZwyTtrKHMqPIiFfojchpGh1Y/pg7j5Dge/4sINPLBaz2+TnqRk8R5iXOdoGs/qtPPji09x8QN/JaSeioeqqKg2F6oKukB9qwQqO41KJ+3K7mXrgfhG/pSkoHLEHm3npHfmm7HsKMRdbgdRwH7YO3xbjDQhjo7n1be9Z3Uj06OYfddon/XmrTrvss+CICCI0SBGN9tn/miRRUP1JIUk8WHSMdb0U5myVWHkQWpdsQ4RPpkisLafjl7x/bhG+n3nePyeCQsw4HLX5a/sxc3DNF8X50SlnUWhV2NN3khMpraxkoN7UpVXwrePPcyU+/9Cly69OD5/Gxy0YVA9Ph0XTpSuepKuGIIp3n95nU6j0km7ki8XAvGN81NiRAhPbrqTBlzFVkrnHMJ+pOWyvRGXdPCDk/YAACAASURBVOODdZnkV9Qp6woCPHNZX58GBQBVe2GppJQ+LL7qA+KD43l98+t8LXzNnnQdQzIU7vyfgirARxfp2NlNx+DYwbwz6R0CNCgFd3J28evBQlz+lbavZdmBQvoNG87hnEy6O9P97qcTRPpGjKWrayCHP1yJGlqCQTBAvSABPQY4CgVvbsUwOZrEC/zLJ+s0KqcYxe5GqXSAXocYZuwQ9Q/aA8Vu5/jCdZhLI1ED3Cgu72z21H4nrwPlLLRQ+K9dKFUthwfrQgwUJQTwr++8Q4uvHZFK/6TwZnp5I7oLgeZXJY1QFYYOGUFiiCfj+bGRj3Fpt0v5Tv6OxeJi7u3hmYFKURJvDbybc1PO9RKF7OT3R6lFu7JxqcVJcnQfPkn8jJez70en0U0eqA+hV1jTmm016AQR1/ISCgL240+se+en+BRhO1xG1bpcbAeKqVFo0IUaCB6RQMiYLoih/smHtwa3283bb7/NnDlzsNvtjB8/nmeffZaIiLYPK1Tsdn577WsyDhsxByVBYBKq8zjUczyadE5ih553UuOoikrJNwd8GhQApcrJom/24Kg3DQwN0PPIBf5nhZtjZXTm3r4bVhNo3k/aCG+Z934x/Xgx5kVeHPciTsWJXtD7t0rq5HdBiEn74zjYKDIxdSIvBc/kjS5f8lDujehbqONywqkQKQoYNE5mBUFHxcIsmOG7VHKnR7CdUVWVsl+OUPTxbmz76gwKgFLppHLFMQre2oo9W5vmjxbeeust5s6dy+uvv86XX37JkSNHePbZZ9t8HJfVxo/3fMzOvK4eg1JNQ3+KSQ1G6DrhpMayHy7Dme+/bEq/PO+CUv93Xi+iQ/zPB0i5bhQmW6Hf7ctS95ESltLseYPO0GlQOvFiZFftZS8GJocTWJ7L9LJSVoZv4oGur7EsbANqPbUIFRWZXVjWvcXxA0tYVuniiN2NonFLN5BgnHt9F6DrNCrtTOXybKrW5rTYRrG4KPpsb6MkvbagqqqKL774gueee46xY8fSt29fZs6cyYEDB3C2cUGwX/76MYXGvo2Ouxvkp1gCxrLhM+3CiF7XaBDZ5Ys0RPpVz+B6xoVw4xhtYbtTBl+JnPwtemfz+k016CvnMejOaZqu30kn3WJDOKdHjKY+X23IIm/rz9xbVs4Iq42jATn8I+lLXkr6iGKxjGKxnFe7fMqDfWaxNPEAPQ7/l9Ci3ey2KmRY8rTfpA/fJXQalXbFXemgYqV/9b9Vm4vyZVltfg9btmxBp9MxYULdymD06NEsXry4TevTlx85Rp69scy7qjqrw4nr0BlS2b9VQXG3Pk7eVdy4lK0vkqo/7s9c1heDqHXvOZA/PvA8uxLfJaxsX5NtTLZiXNYvKL8vkUnpJ7e918nvk79OkTDq/f9s5pbZ+GHtHkwqfFBQyNUVlehVld/CdnJDrye4oddM1oRvA+Df5+koiFDpt+/fBFfloKraJ5WCw3ckwWnxqUiSJAALgQWyLL9X7/iTwH1AKPAT8GdZlsvqnb8DeBKIB1YAd8uy3HJtWD9QnG52r8zCsjGPRKuCCBwLzccwIIaocUkYI1sXkWPeku+ljOsL6+4i3Jc6EEPazr+SlZVFYmIiq1at4r333qOkpITx48czc+ZMQtuwCt+qj+ejiH0aHVdcuXjt+QmBCLporIECu+cuZtD0i1s3YCt2jlRUzu8bz/ierVNnHRw3mHsf/CfPr36SLr/9SL/cQRiVUBTBSUHwYRaOPM5Vf/gTD/S7tXNrq5NWMSglglk3DOW+b7Zjdfo36Sp1B4AOAlSVZ4tLua+snPkhwWQYjLgFSHK5yNLrWRISzLtTRV74ysbAPbMoHHOH5vtzi4pPo3HKjYokSTrgHeBCYEG94/cCDwA3AcXAR8AnwNXV5y8G/gncDuwHXgf+K0nSSFmWtcd7VlN4rIKsj3aS4GwQ21PuwLU2l4L1eQRe2pWYMdoLDdkzmpa6bxa3iiOzgsD+2pbALWE2mzlx4gTvv/8+jz/+OKIo8sorr/DQQw/x8ccft9k4ZSdUqLfwURUzboeM2+Fd7lSnT6194B7acYhB01s3nj4uCEe2nwJe1eTo4MNLGhs+LfSL6cfsaf9l2znbWJK5hGJbMQFiAEPiruOBrhd1Ci52ctJM6h3Por+M5/N1R5m95Vit4KQAnNc3nutHpjBvRy4/7fCoZq9RvEN9Y9wKt5V7fzdsgkCmwcDBJCNzxum4Zm0Jxqw1MFCbTJIjQexYRkWSpG7AF0AK0PCJ+zDwkizLi6vb3gzskiQpVZbl7Orz/5JleXb1+euBPOAcYE1r7qe8yEzOhztIUJqfVQpuFdtPRyjW64gekdhsu6ZQ7Nq3dxRb20on6PV6zGYzr732Gr17e6KXXn75ZaZNm0ZWVhZpaW0jCeJWPUt2VbHhtK5CcRyAJgpgqaoDVVUQBB1Op8ag/HoEj0jAssV/v4qMmwnjU0mLDvbd2AeCIDAsfhjD4oed9LU66aQp0mOCef7y/sy8uA/HS624FIXEsEDCgzwzt3OlOAYmR/DKwv1kKMmsd/dljNj0tix4VjFvFBZxbZcE5o4TGHwEeh5ZT3Gvi4gOSPDrnqqcZQQN7+qz3an2qYwGdgNDgVqPjyRJCUA34NeaY7Is7wZKgXHVq5vRDc4XA3vwGJVWseWbfcS0YFDqY/nlKC57y9UbG6IL1G6zdUFta+fj4jyZ4D161M1IunfvDkBurv/1QXxisqMqVhyVs1Ec+2jKoACorqM4/7+98w6Pozgb+G+vSTp1yXKR3NvYlrsxGIPBpkNoARKwgZBAIAFCC/UjlEBCEnpCQoeEXoLpMSFUm2IDxrjbjHuVZVm9nU5X9vtj9qyTfGVPyNjG83sePZJ2592Z3Z2dd95535lpegfTDOPM77xPx9M3G3c/+8N3/0kPc+kRqW3tq9HsadLdTgZ3z2JYz5ydCgVUx+aCQwfw3AUHUZjp4U/BGbSYib+nAYEgt1ZWE3YY/P1kJw2ZuSxpqieUYKHTCGEzzKKGcvyN8cOVI3yvloqU8gXgBQAh2q0UGxlb6hgmtQ3oDeQD3gTnUybcEqTvNh92B+cNf4jKL7eSd2DyOO0IrsE5+FenMATmdmAWp9PSkroTOh6lpWrDp4ULFzJqlDKTly9fDkBRUZGtvEKhEA0NDQnTGiMg8OX7mOHkGxKFA6sItXQj7+AxSCnt3EZMXEVh0mzENjyPn8ETc9m6YW2n89Jo9kYKgN8f0Z3L3m7ll4FreNj9V7KN+FGkJzQ183V9A6/kZzNr8nh6BAYwr3YVB+UNwu2IHWIfCgeZX7uSSkOQvqqFPgck9jHvLdFfkYHojvu7+lHrBiQ7nzKu8hAZKXp7W7/dVUGYpklLMExdS4jalhBNrSFMK/47bUwhuO0/4vQxhTjSk/cEUqFPnz4cddRR3HrrrSxevJgVK1Zw++23M2XKFHr3/u7LpEQYNmY04cAa2+lD/q/p0z25KR0XXxj34uaESbYT5i58vJwe5IhBXReUoNHsTayqVM3iZ+FRHO2/i38ET2GH2Tb1vclMY0W4ban766trGOZvZVs3Nfm5yjGE92vKWFG3jOZgmy+mJdTMt/UreL96A9sdwzAMg9amvTT6KwYR1ZoGRHuY0oDmDueJcT5lHJ2ZotESIj29TUvXNbdS0eDfJUrD7XRQkOmhKDeTvBMHUvt68sbWmZtG/rEDcaZ3/cz6u+++mzvvvJPLLruMUCjEkUceyc0339zuXhKWzekkLy8vof/l0/mpubVMsxWPr4FBEw5KSS5C1cvf4gu0xWcEMHkOP04MgsC3hPiCoBqEa4E1/hxOGlPcqbw0mr2ZdzevBtTE3HIKuSd4JvcGf0IBDTgIU0M2YRw86r6fo50LSDPh3opK7jDahr0Czt6sNmFVfT2O8FoMIGjk4HAOaaclHDbCnfcWpRIJC+4FVEYd74Ua8qpCKY+OnvJeRPlZUsF0pR7yGXLAlppmCjI9NLQE2V4fezgoEAqzvb6FJn+Q/hN7YgbC1L2zLp6bAVdhOoW/GLnblmrxer3cdttt3Hbbbbvl+gA1cn7KMtVyQaeUSsvaWnwL289uf55WniT+2kmPzFnLiaN76VBfzQ8Or2fX0Q0TB1W0X9fuisClvGr8nuGOTfQNBjkmtIJyjmuXxnDkYDpyMIk9jJWVndz/slcMf0kpy4F1wJTIMSHEKCAPmGeFDH/Z4XwhMBKY25k8Q0VOgqQWieys9lO3rpY1FY3tFUprCGeFD2d5M0bUWlSN/iBltT6yDy2hx1UTyDqkGEeW5UwzwN07i/zTh9DjyvG4u9nYpnZvpqkyeZqOVG9IWcQMhql9o73lt5Uwz+wyMtqe5WX1LC/bfUvhaDR7igP629sptJl0Lmi9hh2mUjZHbFmIx2/f5+sM+uhZ9mXSdHuLpQJq7srtQoiNQDnwOPCKFU4M8DfgJSHEUmARcA+wUErZqXBispzITAelTfYVi6M5SM4ra/GPLqR5Ug+cDQHSF1XiWVWLETXJMdA7k5Yx3Qj0z6amuZXuOel4irzknTSIvJMGYYbCYBg/qBWKHYHU7yUvO3X/UcOcLQR3tHdE3ocvgY3SxtodjbZXJdZo9hXG9smjtDjHVqepjG5c1PpbXkr7I4Fag/5177Jq6Fm28um7+SOcHl/SzY73CkvF4gHgYeAp4ENgBXBh5KSU8k3gWuDPwDzUNoI//i4Z9vzRQHwpWisGkL6kirynJTkvrSZtZU07hQLg3tJE9qyNeD/dhmmaVHdY0tpwOjAcBqGwSUsghK811G5znn2RytqxKaX3OlsZODy1EN9gpY/6j9uvI/YhAb60sac3kPICehrNvoBhGFx7rLC9M/dCcwjXtv6KGoeTkrJP6bP5w6QyPcu/oP/G/1LXWpM07R6zVKSU/Tv8bwI3Wz/xZP4B/CPe+VQZM76Yj3c0U/xxGZkJIsHMHDdGfXvPvsPGxMb0JVWEM1y0TGk/G78lEKKywU+tL7CzoTOA7HQ33bLTOrUE9p5kzXtzacqcjBHejhlcb0tmXME2nMOOS57QwjRNat5cA8E2xdCEyQPYD7/uW/DdJz5qNHsjU0V3/nLaKP7vtaWEbfSd3gpPZlD+bI6hmsFrXyO7YTOb+h5FY1b7iFBv83b6bP6I4m2fYQAbs30k2wBi32q9dgPTjh3Mir65fDVrDSMqA2RFKZdQ/2y8B/eiYGQ3/CuqqX1rndpgKwUyFlTQOLYbTdlpeD1O6nwBNtf4doYdRzCB+pYA9S0BeuSk0yNn79kBMBQKJVx8ct5LS8EzBKe7H0EbSmVQViUHHjoWcuxHY/mWVu4y5+cxWqiyaWkOLMpkfN+u3z9Go9lbOHNiX4b1zOGxT9fxv2XlBKO0yyGDCzl3Uj/mra3i6XlqctczA0cw9YvP8AShZ8V8elTMpyG7L01eNcPe69tBTv36nS1iGFgytkArFTuMGF7EiOFFbK9qZM385bgDzfQaMoC+ot/OaCHvqCLSh+RT8coqgsuTT/CLYARNHMurWet24HY6CNgY5tpe34LLYaS038fuorq6Gr/fH3fxyZVvfky9ZwhmuIlgy7yE13IbIcYWlHFIv0Ycx75suwzhliC1b7fftdFVnMl7O5rAZmj4BYcO0JFfmh88Y/rk8eCM8VQ3tbK+spFQGHrnZ1CcpwKBjhvZiwP6F3DDq0to9niZM8rg6IVtoyU5DZvIadgU89pfCYNAYfKOmVYqQEN1JQvf/Q/LPnoPX4Pl7DIMeg4rZcih0+gxJEo3F4YT7KsWG+emaoIDw7QLxguZpG3x46pRR0NZTvx90zA9ys21ud6gwbtnN3IKhUI7FUq3brsucmmaJl+9sQ7SBhBong1mWwSWQZhx+WWETCeGYVKU1oTI2UFaYQnM+A/k219zrP69je0tRANeK3LRUGbPl3LauBJmHNg3eUKN5gdCQaaHgszYm36dNKaYEcU5/O25d3l2moOB20IMKk98vbICePw4B7/wJveD7vdKZcvKZbxx9x/wN3XYRdA0KV+5jPKVyxgy5QhGn3gahmFgBFN39jZW+nlv2XbVFTBhxHYYvh0yOoR8B76Atd1gYYmaE3PQgAIGFmV1/ua+I263e6dCiaXclrz8Ho1pAwi1riUcaL/cykHdtnDIoCA0V4PDBd2Hw4RbYORp4E4ePm2GTDAgUNZI47z2a5SVDczmrsXJ96nJ9Di5YMpArjxyiLZSNJooBhVlcUUvD5sbAtw+w82F74aZvNLEEaN5+3qwwcM/cpDhCTE2c2TSa+/XSqVqy2Zev/M2Wn2Jd1xc/elHdO9VzKTTz6KpuoKaXRZYTky3Zjj4mxBv0MponIwn9iRHdxiGVUCwIshVNFNJDvcc0DWrCHc14XCYhf/bhunpQaC5ffRIvqeZg6ZOgp88ltI1g1U+Gr8sp3lhxU7LxHA7iHabhDJcXLS+vZLJ97q596dj+HpDDeX1LXicDkb1zuWUsSX7XNCDRvN9Ud3g45rqWi7pUcQDpzh5YarJ1CUmJVUmBlCeD3NGOthWqDpkN1XU4rARMLxff3Fz//1cUoUS4YvXX2b00ceTPjQfXEa7KCQ7DMLJ1dib4DgSF1eTzoIUV0X+PlnwzCya0voSbP4IzPZb7B4zoBLXj2amdL2mr8pVdFeH8Gyzw/L494SaqY1yQLocBg+fM4FJAws5Ypj9xT41mv2dald3jvW18McdVdxSVEhlrsHMKbta9IZpcn11DSc0NTPfhlrZm+apfK/4G+pZPT+xYzmaUCDA8tkf4Mx04x3duZ0DU+Fo3PRx7Z06PxwMsXROHeFgGSH/onbnRudto/f0O8Abezw3Fs0LK6h5bXXSXTIDmHzV2n7m/B9PHcmkgYVxJDQaTTwq+hyP33RxUlMzr2wt5/T6RjLCbZ04t2lyYmMTL5Zt5+x61XEMO5K3SfutUqndvBEznNqEw03LFgOQe9wAnLk2IrMMcPfq3NwIJwaDtrcQshN0/j3zxRNv0OzpTqDp/XbHM11+Dju8FIafZPtaZiBE7dv2lqR3Y3BR1Jqi5x8ygLO0A16j6RRTx4/grfBkAAYHAvy+qppPNm3lrS1lvLmljM82buHPO6oobVVD0R+ExuFyaqUSl2Br6nuWRIbKnDkeii4ahat7/OEsI81J4bkj6HHFeHr8dgKefjlx08bDt62J6Y9/QVlt+yG6QChMWa2PrbU+WoPf70z8UCDIyi9bCbXM32XvlCP7VZB2yn0pXa95cSXhZvvDfNNwk4fB4UOLuPGEZBHzGo0mHn0KvHw64CpkuG3CY7ppMiAQZGAgiDdqLt0WsxsvdL8ap42lpfbO8ZXvAXdG6nuJe6JkXIUZ9LhiPL4VVTR9VU6grAkzZOLKT8M7vjuZE3rgsHZqc3f3ki7yad2Y2oKGBvDV+mqO/9un3Hn6KIb1zOGpuRt49ZstNLSohjjD7eTUccX8fPIARM/dv2fI5w++SrPLRbC+/cJyQ7IrGTL9ZsjcNfQ4ES3f2p/zA+DB4MScTK6bMQ6Xc7/tE2k0XcK1p07i5w/+kf9r/RtHORfGTDMvNIKbHJfz0E+m4itPPqqw3yqV3N4DULdvv5e8bc0aylZ9S/FQ1UM2nA68o4rwjipSM+RNE8MRu6FzFaY+Qz6yLlmdL8Cvn/sGh8EuSzD4AiFe/Goz//56C3ecOrLLh4NCoTAb3ltE7YYdhE2TlYvdBPzvEr2Ov8cR5IhDBsDI01O+fipWSoSLJvYlJ73zWxFrNBpFnwIvj/36aC58Jp+/VEp+6pzDYGMrBiYbzJ7MDB1GTc5wHvvZAYie2SxKMp8F9mOl0lzlwukZRqh1mW0Zf1MdL95yLRNOOIVDzjwH0zRZ+elslnz4Ljs2rscMh8kuLGLEYdMYfdRx5HTrvlM2fXghRroLs8V+I3o8bqoxeQo/rbQplJE46YcDA7Xs+yJChMImN7y2lDyvm+NGdtx2JnVCoTBz73+L5cvKaQltwgzXAgYmYcxQ+5Dew0vKyTrjKWyvaBdNJ1ZqLixI3crUaDSxGVSUxXtXHsYHK4fx8vxxPLujEdOE/oWZXHRAb44b2ZM0l/0p30bHNaj2BxYsWFC74+uq3DULWvDXv7BLSKwdsgu7EQwE8NXXxTzvdLk4+qLLKD38yJ3H6t5dT8PsLTHTJ2I9If5CC/1xMB0P/TvM6S8jzMv4eY0AxXkZfHLdNFtjn/EIBYK89JtH2d6wCDO0LWHa4ow6zrriYoxxM3YeM8Mm/tU1NH1TQaimBRwG7p6ZZE7siadETeY0g2EaP99Kzf824kghGCGESberDyCzSCsWjeb7ZtGiRYRCoboJEybEXa9lv7VUXNu3YTj64Mn+CYHG162eeCwMDGcRZqii3dGGqsSbUoWCQd596H7c6ekMPegQAHKO6kfrpgb862IrongMwMkjeDHirKRcjIOryGAULm6v9fHxtxUcNaLzczbeuOExyus+AbMpadqsjNEYY6fv/D9Q3kTVCysJVrQPLmjdUE/TF9tIG5qPd0IPGt7fSLDSl3KkyDyCFFTUc4xWKhrNXsl+6+lMcyil4HDm48k5F5f3WAxnL3Y+EiMLZ9oBeHLOJy3nHNyZJ4KRekP24ZMPEwyoVQ8Nl4NuvxhJ5kE9wRlbQaQNyyf35IEYGe31fTyFEs1RuDmfND5b04ldGC2attewadtSWwoFYH19GqGAWoMrsL2JikeW7KJQovGvqqHmxW8JVtqbdBpNMyaP4qc8zjbOGo1mz7PfWioV2RXk1a6iNm8ohuHGlVaKK61055L0HdeKcnqG4nD1IdD8AeHAatv5NNfVsvrLzxl+6FR1XbeDtCO7syawmLp5G0lrzcAwDPyGj/Qx3Sg9fgjZPXriHVVE7Ztr8C1LLTrqp3j4V5PNpXtj8P7fnyEcSr6uVoRAcC1fPP06k395BtX/XpWSzyiCD5MVhJiQoDo2YHIjzawnjEdHfWk0ey37rVIpG1xA6cz/Ups7GIy2RirRwoOGIwOne2BKSgVg3TfzdyqVLSuX8eZdt9HSHKOn/j589eFMjvn1FZQefiSF54zg40cWMGRDs+28vBgUbmqkviWwM0KqyR/kzYVb+WruZowav4opK0jjoMl9OGVcCV5PWzXYtnFVu+ulObz0yxpBljsP0zSpD1SxqWklgXBkZnuIb+fP44CjjyGwNXXf1AcEeIgWKjAZhZPT8TAVFy7LMqshzH8I8CqtVFrRcHpLYI1m72W/VSoubw7f9F/NuFUv8u3Q6e0US0cyGzaD4aApqwTTTH3oZd2Cr5j/9mvkde/JOw/cSTAYf8n2cDjMuw/djyc9gyEHTaZvURakoFQA0mv8TLnzY351+EDG9s7l7WcW89OWVg5zZENkMcvtJhUzl3P7rNVM/+UExvTNByAYUvfnMjyMLzyKvlkjcBrtAwPGFkxjbcNillTPJkyYgL+R5sU7UiojwNP4eZy2ZVeWEmIpPtKBAgxCwA5Moqd3ju6dq5WKRrMXs98qFZEpuOkQF2Oencu4RRVs7Hcs1QUj2qVJ91XSe+snlGz9GL/bpCFvPCv6laYws0XR2uLjk+f+mZLM+w/fx8AJB1Lo9ZBq/38iTj7zBbn3Xckfgi1c6uoOjl2XlenuzOY3rfDJg7NxXngIq5/+N4GwD7fhYVqvGeSnxXb2uxweRO5Ectzd+Gz7TNI9LupX16S8z0xznF0bW4CyOOcuOyK1fe01Gs33y36rVAo8BUwcOo3bZnzIta+uYeySNfjSC2nI6o3pcJHmryW3bh0+j8l9pzlY0t/B1KULmbQmg427f+I6Pl8La+bNpiR3RPLEHSjByT14aTFDpLuSLw9zmNGNRXc9xbq6TwCYUHRiXIUSTS/vAE7sczEZriyoTN2CCwAjeuXws4P78dbiMuauTew/uulHwzn6O0S1aTSa3c9+q1QALhl7Cedum8fNP2tm9HqToxZWM2B7Fe4QVGbD6xMdzBnloDndYGDuQGYfuJX8gAtvfX/CwQ27vXyzn3qCiSecSTczH4eRqh0A6SnIDMsdzeq6z0lzeumTOdy2XIar85uI9R3WjTvPG4thGJw2vjdPfLaOZ+dtZFtdewV1QL98Lp02mGnDuse5kkaj2VvYpyY/CiFcwL3ADJRCfBa4RkrZmlCwAwsWLKh1Op25Y8eOZV7ZPK78+Eqag/H9FmeKM7nxoBtpDjTz/E3X0Vp9GK0NL2FniRdn2gQMI52gfwmYDakUcycHFf2I/lnJd1z7rgTCfhw4cdpY3vq7sp4Q3x7fhwsPH9TueDAU5sv11Wyt9eF2GpQW5zK0x/dgGmo0mqT8ECc//gk4HjgZ5XF+GmgFrunsBQ8uPphXT36V51c+z5tr3qQh0NbwTy6ezNnDz2ZKyRQMwyDLk0XxESMof9mDmXUKgca3UIM4sXGmT8KVfrCKKDPcBH2zO1XGhVUfUuDpRY4n8b4hzcEGllZ/Qi/vQHpnChwJgg9i4Y7hd7HLekL4MRlms0o9jZ8ZPXa1clxOB4cMTm1RSo1Gs/ewz1gqQoh0oBKYLqV82zp2EvAiUCSltD2bLtpSicYf8rOlYQuBcIDu3u4UpO+60dTG+o3MvuBeGgtPxQzVE/QvJNS6HHZGhTlwuAfjSh+Hw1VCdv068qo+oCZ3HJXGp528exXaO6n7SfTM6B/zfFVLGXN3vElzUK2EfEDhcQzKGdPp/FJhJn5ezjWoqGvhD2RwGIkXe3ycFt7LdfDpddP0SsMazT7ED81SGQtkAp9EHZtjHRsL2N/GMQ5pzjQG5Q1KmKZfTj82TN2O+HgxVd3G4PYejitjCma4AQhjODIxDBW2m95SxRbvU9Rc/RNaX/oaV1lvwkG7a395cKaNIxxYixmuxB9uZk75y+R7ejAgezQ57gLAoDFYy/qGpVT5t7aTbgqmthTMd+HAyX258uShXPrCN9y0ZBtnEOIMPBR3WLBhBSGew88nSFiWhAAAFINJREFUBLl5ygitUDSaHyD7klIpAZqklDtbSyllvRCiGegdXyw2oVAIKWWnCjJx0nnM2ngjxyw/nrLiwwg70zCc7edOFFYtpcL9Ip6fnc5xWcdRduoQ1jy0mnq2AfHnqUTwZEwly7eUoNGHetqWXalp3U5N1fsJJMFwlrC5pZLRKdxT2AzzdcOHDDjjdAreq8NpY1kYgEZMcgeoZ3nBqHRWbU3j31V+ZtLKaJz0xEEIk3WEWWvNODlqUDaTu/k7/fw1Gs2eIRRK3nbtS0rFC/hjHPcDnXcGdIJBWYM49LTrebroLo798j0G1E7A5+1N2HCS7q+m0ZjP+2OrKJl2OtOL1da6xd0GsS7tVdzppxJofBvlCoqFgct7BHlNGxl/25WUr1/G4mc3Y4ZtrudlZFMwIZ+srEK2Ll9PiXeALbGy5vUU//ggvCXpyNx6Rtg0dNYXOxnoURZHpsfJXceX8MT8Sj5Y08CiUIhoBZqX7uT0kXmcMTIPR2eWyddoNHs9+5JS8RFbeaQBqU05B5xOJ0KIThdGIDi09FCeP/x5/r30dXLL5+IKQ1Weg1Ejj+BXw89mYs+J7WTM2y5j0WWPUll0LsHWpYT8y8CMFN2N0zMcZ/pYuletpOi6iZQOL6V0eClrXvqKRn8VxJkQGI3X2YfzfvtnDMPg6fOuI99TiDfJXJWmYB2yfjnnHX03AP0uG8Die76ipCVxfhtzXRx7yYE4Ouy18OBIqGsO8N9l29hS48PpMBA9szlyePeU9mXQaDR7F5ZPJWGafclRPwnlN8mRUjZYx3KAOmCSlPLLRPLRxHPUd5bWUCtljWUEw0G6Z3YnxxO/Ef96zScsu/F+0s2pVOaPQBlaYTAyyK3fiLtpNlnXHsmJU36xU2b12gV8cMt/aA5+Q/yhM4MM1wQmX3kwYyceC0D11k28cf0jTCgaQ2FacUypypatLKhcwhn3XEZuz7bNvVqbW5n/5BKKtzbj7jAU5sNkx+AcJp03CodbKwmNZn/hh+aoXww0AVOAd6xjh1vHFu+pQgF4nB765/a3lfaAwYcx4OlS3pnzOMy8k6yqbAwcNGfW4zt5DIedcAf9cvu1kxkyaAL+3/n4/M8BfECodQVtw2dqB8uMcDrjLp+wU6EAFJT05dS7Lua1a+/H48lggLeELLda46shUM2GpjICQR9n3H1NO4UC4PF6OOSyA/DX+1n+4Xp8FT4MAzKLsyg9oj9DvHo7X41Gsyv7jKUCIIS4HzgFOA8wgGeAl6WU16dyna62VDqLaZr4gj7CZphMd2bCFZIBWoItvPfff1L21lqMFmsHRU8TRcf05LjTLibTnRlXdtOiBXz2+Mv46tWETW+OiykXz6D3yD37DDQazb7DD81SAbgByADeRk1nfx743R4t0XfAMAy8bvsbf6W70jn5pEvgpNTz6jt2AjMenJC6oEaj0aTAPqVUpJR+4NfWj0aj0Wj2MvTsM41Go9F0GVqpaDQajabL0EpFo9FoNF2GVioajUaj6TK0UtFoNBpNl7FPRX91ITmhUIhFixbt6XJoNBrNPoO1REvCdZ/2V6USBhyhUKh+TxdEo9Fo9iFywFpuPA771Ix6jUaj0ezdaJ+KRqPRaLoMrVQ0Go1G02VopaLRaDSaLkMrFY1Go9F0GVqpaDQajabL0EpFo9FoNF2GVioajUaj6TK0UtFoNBpNl6GVikaj0Wi6DK1UNBqNRtNlaKWi0Wg0mi5jf11QMiZCCBdwLzAD9WyeBa6RUrbalDeAd4BZUsp/2EjfG7gfmAYEgVnA1VLK2iRyQ4EHgEOARuAp4GYpZdBmOf8EzJBS9reZfjLweYfDTVLKrAQyTuAPwPlAOvAucImUsjpJXj8H/hXn9OFSyk/iyOWgnuXJ1qFZwFVSypok+RWgnuVxgB94FPijlDLmonnx3rEQ4nfApUA28Cbwm+j3mKxuCCGeBHZIKW9Ilp8QIh+4CzgR8AAfA1dIKbcmketp3esxQAh4BVW/G1Mo50XAo1JKw0Y5i4GtHa8BFEkpK5M8z6uAK4FC4FPg11LKjfHyE0JMtZ5DLM6TUj6ToJwe4A7Ud+8FZgOXSyk3J7m/DNR7OAPVXrwAXCel9Cf6tq26+iBwEtACPAT8QUpp2mkTrPJ+DdwopfyPdSxRfiOA+4BJQAPwEnAz0C2BzEGotnAcUAH8Q0p5b5zn2w5tqbTnT8DxqIbpVOv3n+wICiEcwN9RjZOd9E5U45OFeqknA2OBp5PIuVENdA0wAZgOnIOqJHbynQBcaydtFCOApUCvqJ+BSWTuAH5hlW0aMAx4xEZeL3fIpxfqfr8A5iaQ+wcwGvX8j7P+fsJGfq+hPpxTgB+jGog7YiWM946FEJcAl6PudxrqeT2RTC7q/I0o5WsrP5TSHWuVeSpKkb1l1alEcjNRjfQU69zBqMbNbjn7AHenUM4RQC27vs+qRHJCiF+jOiS/BQ5ENdivJMlvbox8HgfWAW8kKedNwGnAWcChQGZEJoncI6g68wvgSFSde8rGt/0EMBj17i5EKc9L7bQJQoh0lFIYFXUsrpwQIhv1/ZSjlMrPgNNRyjCeTBHwX+Ar654uB24VQvwCG2hLxcJ6WZcA06WU86xjlwEvCiFullL6EsgORL34PqiPyA7jgPFALylluXWdy4HPhBB5CayVEmA+8CspZT2wSgjxCqpi3JrkHj0oq2Yu0M9mOQFKgeWRcibD6oldCZwlpfzAOnYV8KgQwi2lDMSTtZ7zzmcthDgVdW+lSSyxk4GLpZQLLLl7UFZHonKOAw4HxkspF1rHfgV8LIT4g5SyOSptond8Ncq6+Z+V9jxgiRCiL+obiyknhOgOPIlq3Ld0OBczPyFEN5QymSSl/Mo6dr4lP1II0RBHLhvYBNwipVxjHXsSuMbG/UV4AlgEHGbzuZQC38aqNwnuz0A18jdJKV+1jl0MfCSEKAHSYslZownlUdeZgFLUU6WU9UnKeTLwhJTyU0v298DnQohCIDdOOQuAc4HTpZTvWsfORr2Hl4j/bfdDdVzGSCmXAouEELcCV6E6TnHbBFRH7mmUlRlN3LYEOBa1XP2vpJR+4FshxM3Aw6jOSCyZvrRZLSawVgjxAeo7jDeKsBNtqbQxFtVDiR5emWMdG5tEdhKqJz8eqLOZ33rg+A4fXGQfgvR4QlLKDVLKMy2FghBiPKq39JGNPG8B1hDV67NJKfBtCumnoPZcmBU5IKX8WEo5NJFC6Yg1HPkX4K9SyrVJklcDM4QQuZZSOwulfBMxGPBFFIrFIlTDdUCHtDHfsTWkNJCoemM1FjWo4clEdaMUNRwxBtjY4Vw8OR9wglXOCJGhuox4clLKBinljCiFMgQ4j7Z6k7AOCyF+CRSghlHslDNyf/HqTTy5EaiO0846KqVcI6Xsaw3v2f3W7gJmSik/s1HOauDHQoieQog0VG9+DeodxpMbBBhEWc9SyjJgh1X+eN/2wUCdVUcizEHVoeYEcunAEcBb1jWiSdSWzANOtRRK9DkXcEIcma1SynOt4ThDCHEEyqqy08ZoSyWKEpSfIPpDrBdCNAO9EwlKKV9AjacihLCVmZSyCmWWRnMVsCYFi2A56iNcANyTJO144CKUOXuGrUK2UQo0CiEWo4ZP5qB6MfHKORjVKz7R6oUVoe71t9HP1wZnoHqId9lI+2uUD6wG9XFsQDXqidgOZAghCq33gZUfQPfohAnecYn1u6PvYBvQW0p5dxw5pJQfY/kBYpyLmZ+Usgk1NBHNb4F6YImU8ot4+UUQQsxCKaYNwI1J7i8y7PVnVKPWzsJNUvdLgSYhxJeo3u/XKD/XmgRyg1G+rYFCiJlAf1TDfZmUsszOtyaEmETbMKSdcl4NvIp6ZyFUHZpi+dXiyW23fpdE/hZCZKIUrzdivURxFUpRlRC7rgBkxpOzvrWd33iHOpGoLdkanZ81VHY58LmUsmM9atf+WFZjA6pjPQt4DhtoS6UNL6oyd8SP6rnuVoQQ16PGOq9MQexc4GhU2V9LcO3IsNe1dhVWlGwuUAy4gV+ifCQDgHct/04ssi2ZW1AN3gxUT+/FVPJGDUc+lcy5bzEEWIka2z4SNVTxnPVhxONL1Jj7I0KIPGtI4z6U09Jjs4xe63fHuvN91ZuzUM/4hujhuiTcgPIdbAXeS/AeIzyOctQuTZKuI8NRdeFqlDVtAnOsoZx4ZKPapcdR/sxTUUNQ71qWqx0uAf4rpbRrXQ9EOaNPRD2XhcArQghvPAEp5SZU8Mr9QohelkL5q3W6Xd3p8G3Hamci/6clkLNNErm/o0ZerrMh40BZKD9GDbE9ZCd/rVTa8BG7EUhDmaW7DWuM8y/AlVLKWcnSR5BSfmP5LH4OHC2EKI2T9GaUSZswCCBOHnWoj/pUKeV8KeVsVCUbhfJHxCKAahx+LqX8SEo5B7gAOF4IMdhOvkJFDk0hSeCClXYw6mO5yBpmm41yvB6RoIxYQwKnoXrU1aghqNnW33a3mo74fzrWne+j3vwc1Xv8q5TyYbtyUsqlUsrPUZbgcFQ0WLw8LkA5vW0FrHSgN8qn8ZllQZ2JanATWcoBVAfmeinl21LKL1HBKKWoBi4hVgfqx9ioN1b6HCvtLVLKWVY5IxbyT5OIn2OVtQyoRNWZRUTVnRjfdqx2JvJ/cwI5W8STE0I4hRCPogIDpkcP+caTkVKGpJRfSynfQFkx51udzIRopdLGFiDTcmgCOyucl9hhkV2CEOKvwG2ocNsHbKTvLYQ4rcPhZdbvojhi5wDThBCNQohGVKhgX+v/KcnylFLWSylDUf9vR0XwxBsWLLN+L486ttL6bTdA4ATUO0nmFwFlBfmllKuiyrgR9aEnjFKTUi6WUo4AeqKe38Oooa91NssZcbD36nC8F7u33lyFcpreLaW82kb6AiHEdKEimQCwrNYq4tcbUHVnGFBj1Z1XrOs1Wo7puEgpm6PH8qUKwlhP4uHkSN2J1GmklDtQ79JO3TkMNaz/jo20oO4tE1gclV89sIrkdWeDlHIyKjS3yHoP/bDqTpxvewux6wpY955qmxAhnpxlib6E8qGdLqV8PZGMEGKoEKJjpNsywAnkJyuHViptLAaaUL3jCIdbxxbHlPiOCCFuBy5DxdHb7WkKYKZQcekRJqKGFlbGFmEqMBJl9o5FjY+XWX9/naSMk4QQDVYkU+RYX9SHFC+/iPNyfNSxiBVlt7E+GPjEij5JRhmQLtT8nUgZe6D8P3Ed/EKIfCHEp0KIflLKCillC/Aj1Bh3vHtrh9UwryOq3gghRgF5KCdplyNUtNd9qAip/7Mplo/yDex08goh+qMUyooEcueg3l2k7lxuHR+LchrHK2OJEKIuutNiddiGkvjZLkT15idEyXVH1Tc7dedg4BsZNfcmCRElNiYqv3SUQklUdwwhxP+EEJOklFVSykYhxIEoC31ugm97LlAg1NyRCIcD66SU5Z1sE5K1JU+i6vWJUsq3bMhMAV7uMPw3ETUnblOysmhHvYWU0ieEeBz4h1AhoQZqSOVBq7HpUoQKZ/0dyvn2vhVFFKFSxg+f/QSl5J4RKgSwCHgMeMyyIHZBRk0as/KuBIKRSKAkLER9eP8UQvwWFYXyADDbGpqIld9aIcSrlsyFQKtVxneklOtt5AkqoCCun6gDX6CCFf4phLgCFQ11L0phfhpPSEpZYzUg91tjygNQ8zZusqnMIjwA3C6E2IgKa30ceMUad+9SrHryd5R/6skO9aamQ5TPTqx3Mgt42BrSAnWv/5NWaHIcuXbWlhBimHU8Yd2RUm4VQnwDPCDUvBMfagitnATv1WqcHwLuE0LUoOre/SirN+bE1w6MJsrKSYaUcosQ4k3gb0JN7KxC+QJ3WmVx5EwhRD1wj1Bh6DmoQJG/oupRvG+7DDUH5hlLrhfKUvhdZ9uEJHIHonyvlwHLos6NTCDzplWmfwoVaCNQwTJ3yDiTgqPRlkp7bgDeA95GVfw3UQ9+d3A66vlfh+oZR/8MiyckVUjuSagIlc+Af6MiM67YHYW0GqnjUR/ZHNTzWUXyCLLzUA36LFQo4jKUw94uPVC+DTtlDKJ6YhtQwx7/Q328P7LxEfwUNfyxEDWZ7TYpZcL5LTF4ADVs9hTwIarnf2GK17DLiagh2ensWm+OTiJ7Dmo48R3gA5TFcNZuKieoZ7sE9T3NQ0VWHSuTh5Vfj/JzPIuagNeCCpntOD8jFrbrTRTnop7HiyjnuxflC0rmE7sYVc/moiaWPo9qL5J92+ejrKBPUB2Q+yxLoVNtQhK5n1lp/t7h+PsJZHqi6lIhqmP2sCVvJwoTwzRT6ZBpNBqNRhMfbaloNBqNpsvQSkWj0Wg0XYZWKhqNRqPpMrRS0Wg0Gk2XoZWKRqPRaLoMrVQ0Go1G02VopaLR7EaEEKYQ4sQ9XQ6N5vtCKxWNRqPRdBlaqWg0Go2my9Brf2k0u58DhBC3oNalWgNcam0HENmv5o+oJfjzUUt3XCGllNZ5EzhJSvkf6/+pqI29sq11skxL/iLUulrjbS5notHsFrSlotHsfi4Gfo/ag2Yd8ELU5mEzUbsUTgcOQq1z9V6iDaJicDZq75jztELR7Gm0paLR7H7ulFK+AyCEuAu10GaRtaT7UcBEKeXX1vmzUZuFnY1abNAOj0kplydPptHsfrSlotHsfqL35ai1fmeg9ilpRS3bD+zcg34hbfvPpHp9jWaPopWKRrP7iTUkZdC2FXGsc/G+zVijC/Guo9F872ilotHsOVai9myP3uXQi9qF8FvrUCsQvS94wi1uNZo9jfapaDR7CCnlaiHEa8C/hBCXoDZeuxVl2bxkJZsPXG3totgLuGaPFFajsYm2VDSaPcv5qN0N30Jti+wFDpNSRnYv/A0QBBahtki+YU8UUqOxi975UaPRaDRdhrZUNBqNRtNlaKWi0Wg0mi5DKxWNRqPRdBlaqWg0Go2my9BKRaPRaDRdhlYqGo1Go+kytFLRaDQaTZehlYpGo9FougytVDQajUbTZfw/kum5MBroGnYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax = plt.subplots()\n",
    "sn.pointplot(data=hour_df[['hour','total_count','weekday']],x='hour',y='total_count',hue='weekday',ax=ax)\n",
    "ax.set(title=\"Weekday wise hourly distribution of counts\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "+ Weekends (0 and 6) and Weekdays (1-5) show different usage trends with weekend's peak usage in during afternoon hours\n",
    "+ Weekdays follow the overall trend, similar to one visualized in the previous plot\n",
    "+ Weekdays have higher usage as compared to weekends\n",
    "+ It would be interesting to see the trends for casual and registered users separately"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Text(0.5, 1.0, 'Box Pot for hourly distribution of counts')]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax = plt.subplots()\n",
    "sn.boxplot(data=hour_df[['hour','total_count']],x=\"hour\",y=\"total_count\",ax=ax)\n",
    "ax.set(title=\"Box Pot for hourly distribution of counts\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "+ Early hours (0-4) and late nights (21-23) have low counts but significant outliers\n",
    "+ Afternoon hours also have outliers\n",
    "+ Peak hours have higher medians and overall counts with virtually no outliers"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Monthly distribution of Total Counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Text(0.5, 1.0, 'Monthly distribution of counts')]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax = plt.subplots()\n",
    "sn.barplot(data=hour_df[['month',\n",
    "                         'total_count']],\n",
    "           x=\"month\",y=\"total_count\")\n",
    "ax.set(title=\"Monthly distribution of counts\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "+ Months June-Oct have highest counts. Fall seems to be favorite time of the year to use cycles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Text(0.5, 1.0, 'Winter')]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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iBKNGjWqkVBmTufx01J9e35OJSA/cWhHdgK0xwROAyar6shd3JLBMRA5R1bVe+KOq+owXfiFuyObJNMJyxoFAgBHHFTFnqZtJ46JeRVZ9z0Bz59oYE2NSyVefioj0BK4HjsF18n8CzFDVd5I8RF9gOW7hon9HHfcgoAdR03+r6nIR2QL0F5GvvH1nRIVvEpGPaKRCBaBnxzzu/1FxY5zapJCqMnv2bD799FMqKyvp0aMHI0aMoHfv3o2dtCZt754dbN/s1obfG+e5k83rl5OXm0urdj3IK7DnTpqLpBs0RWQwriBoj5tccj6u72ORiPyotn0jVHWeqo5R1c0xQZHFwONNEd4VaEv8uZAi4SmxePFihg0bxrBhw1i8eHGqDmuasEWLFnHBBRewdetWzjzzTAYNGsTOnTsZMWIEb731VmMnr0nbvnk1i1+6gcUv3cCSv1d/VnPJ329m8Us3VBU8pnnwU1O5C9c8dXv0RhG5Bbd41yv1SEdkkqV4U4QXJBHuW+yaE+FwmPvvv5+SkhIAHnjgAW677bb9mrS6deuWdClsaztkhqlTp/LTn/6UYcOGVW37wQ9+QNeuXbnnnnv2W3grWcmsOWFMtvIz9OK7uOkjYj2Nm4qiPiJLpsabInxXEuH1FgqFqgoUgI0bN9qXQzPw1VdfxX1qfsCAAXz++ecNnyBjMpyfmspa4ATcanbR+gAb6pmOyLDgzkBJ1PbOuCavTbjCI94U4m9QB7FrTuzdu7danCOPPLLaE8FlsQ13NYhep6GsNEHkOPuYhnHwwQdTVlZW7f/+2Wef0aFDhzp9HsmsOWFMtvJTqDwEzBKRrsA/vW39cM+NxHuGJWmqul5EVuOm/14OVYMC2gDvqmpYRN7zwl/wwtsDxwLX1OfcpnkbPnw4t912G99++y3HHefmm1q6dCmzZs1i9OjRjZy6zJGTA21awtYd7nWblvaEfHPlZ0jxDBFpBdzIvifo1wG3Rj/AWA8zgDtE5AtgPfAYMN8bTgwwHXhaRJYDS4H7gQ9Utc4jvyr3lFNR4p6ajjd6pXzdBsK5ueQe2Jacgvy6nsY0YRdffDE7d+7k0UcfrXqCvmPHjowdO5aLLrqokVOXOQKBAGecmMfLi12N/4wT82yIfTPla0ixqt4lIvfhahC7gZaq+k2C3ZI1A1dYPQHk4WZFHhN17udF5DfAFO/8rwHn1+eEFSVbKP3r/7q/K6s3V2z72/+RmxOk+JwzyO/SqT6nMk3YlVdeyejRo9m+fTsFBQXs2rWLjh071rqPrfpZXfeDc7ji3DqNmzFZxM80LQfjOuXfUtWbvG2fi8hS4BequtHPiVX1sJjXYWCS91PTPjOBVNSKjAHg22+/Zfz48fTp04fx48cDMHDgQI466ih++9vf0q5du2r7JDvNuzHNkZ9Wz4dxneW/j9rWGzesN+Oncw0GcugYNW1qpxatCAasUTjb3X777RQWFvKzn/2satuCBQvIz89n8uTJcfepaZp3Y4y/QuU04BpV/TyyQVW/AK4DzkxtshpeIBBg9An9OLCoJQcWtWTUCf3szrMZeP/997n55pvp2nXfM7RdunRh4sSJ9vCjMXXgp09lN3AwoDHb2wNZMX7yuIO6MHPITxs7GaYBFRYWsmHDBnr06LHf9q1bt5Jjw5eM8c1PofI08JiIXAv8CzdLcW9gGm7KFmMyzpAhQ5g0aRI33XQTxx57LIFAgBUrVjB16lQGDRrU2MkzJuP4KVRuBNoBC4Cgt60SNz39dSlOlzENYsKECZSWljJ27NiqBxZzcnIYOnQoEydO3C9u5Z4KKjbuZG9F9Qdly78uJZybR26HFg2SbmOaKj/PqZQBI0VkLHAkbi2V1aq6Izqet5DWM6q6PaUpNSYNCgoKuOeee5g0aRJr1qwhLy+Pbt260aLF/oXD/Pnz+eFx/Sn/+xdUVFbvlN/6l4/Jzcml7U+ObqikG9Mk+V5OWFW34Zq/ajINtyqjFSomY7Rs2ZKePWuewm7KlCn0nvUUNoG7MbVLR0+kDZkyWSccbvDFRY3JSDa8xRifgoEgHYvaVr3uVNSOYCBYyx7GNB9WqBjjUyAQ4NJe53DgAW048IA2XNLrbHumyRiP7z4VYwwc1/E7zDij+qDHcDjMlClT6NmzZ36fPn2qtovIzcCvcaulPg9cpapbo8J/iZvxuxOuT/IKVf0KYzKM1VSMSZHKcCV3/+5+li5dut92ERkDXA1cCpwOHI0bih8JHwI8CNwA9MVNqPoXEbHqj8k46aipWI+myTqJmrfWlW7g7ldnU1K5vdpwZGACbinulwFEZCSwTEQO8ZZ2mAA8qqrPeOEXAt8AJwN1XtrBmMaQjprKHtxDkcZkjfz8fHJyai5YVnz7GT3adeXPs56kqKioaruIHAT0IGqFUlVdDmwB+otIDq52Eh2+CfgIV6gYk1FqramISNJPcqnqSu93h/omyph0+vTT2BWxa3bEEUcA8M9//pPyr0rZwta48c44sh9nHNmP4tbFsUFdvN9fx2z/BugKtAWKagk3JqMkav76CNecVdMtWiQszL6pW4xp0s466ywCgUCNz55EwgKBAB9//HF9TxeptuyJ2b4HKEgi3LdQKIRq7LyvqdWtWzdf8Xft2uU7/pdffunrPPXZxyQnMpVRbRIVKt1TkxRjmo6FCxc25Ol2e78L2H+WiQLc+kTR4cQJNyaj1FqoeOul1EpE8oE+QMK4xjQFXbp0SRinvLycFStWJBU3gciw4M5ASdT2zrgmr024wqNzzH6diepn8SMYDCIiddnVl7LS5ONG+pm2bks+ftV72NlA+5iEli5dmrC24mc54X7ALNxwyNgO/rCfYxnTVHzwwQfceuutfPbZZ1RW7j++JBAIsHLlynodX1XXi8hqYACwHEBEegJtgHdVNSwi73nhL3jh7YFjgWvqdXJjGoGf0V8PAhuBX+Cq7BfhpsPfAQxLfdKMSb+7776bdu3aMW3aNAoLC7nvvvsYP348RUVFPPDAA6k6zQzgDhH5sYj0AeYA873hxADTgbEiMsIrcOYBH6iqDSc2GcdP7aIXcJKqLvMW6vpWVf9HRDYA12ILdZkMpKr8+c9/5qijjmLOnDm0b9+es846i/bt2zNnzhwGDx6citPMAA4EnsA92Pg3YExUGp4Xkd8AU3A1mNeA81NxYmMamp9CpQKItIj+BzgeN53Ea7hajDEZJxgM0rKlm9D+sMMO45NPPqFfv36cdNJJ3H333XU65syZMwmFQuWR16oaBiZ5P3Gp6kxgZp1OaEwT4qf56z1gjPew1odA5BbuWNyCXcZknOOOO4558+ZRWVnJUUcdxRtvuL7xVatWkZeX18ipMybz+F1O+CVgA/A4MNHrgOxE1DxGxmSS8ePHc9lll9G+fXuGDh3KY489xsCBA9m0aRNDhw5t7OQZk3H8LCe8WEQOA4pUdYvX4XgBsCkyZ5ExmaZXr168+uqrlJWVUVxczIIFC3jllVdo27YtQ4YMaezkGZNxkm7+EpFXgTxV3QhuqKSqPgy8KiJL0pVAY9Lp4osvpqKignbt2gHQoUMHhg8fTt++fbngggsaOXXGZJ5Ec3+dhnsuBeBU4DIR2RET7bvA4alPmjHp8d5771XN/7V48WKeeeaZ/SaBBFi9ejVr166Nt7sxphaJmr82Adfh5vcKAFcB0Y9ThnHPqUxIS+qMSYM2bdrwhz/8gXA4TDgc5k9/+hM5Ofsq7YFAgKKiIiZOnNiIqTQmMyWapmU5btpuROQ14AJV3dIQCTMmXUSkav6vESNGMHPmTIqLq80ubIypAz8d9acDiMhA4Bhcf8zHwEJVrUhP8oxJr7lz5wLw7rvvsmrVKiorKzn88MPp168fubk285AxfvmZ+6sTbm3t3sDnuOawQ4FPROSHqrohLSk0Jo1KSkoYM2YMK1eupEuXLoTDYdatW0f37t154oknaN++fWMn0ZiM4ufhxxm4p+q7q+qRqvod4DBgMzAtDWkzJu0mT55MMBhk4cKFvPzyy7zyyissXLiQNm3aMGXKlMZOnjEZx0+hMgi4WlWrVqhT1XW4Tnob0G8y0ptvvsktt9xCp06dqrZ16tSJiRMnVj1db4xJnp9CpQw32iuWrfpoMlZBQQGBQPWFTQOBQFKr3Blj9uenUHkFmOb1rQBV/SzTvDBjMk7//v2ZMmUKJSX71s8qKSlh6tSp9O/fvxFTZkxm8jO85Te4WYm/EJHIKo+HAsuAq1OdMGMawvXXX8/IkSM5/fTTOfjggwFYt24dIpLK9VSMaTb8FCrzcE/Vfx83pHg3bkjxMuDvuCWFjckoEyZM4KmnnmLZsmWsWrWKwsJCDj/8cESEX/3qVyxYsKCxk2hMRvE7TculuCfoI1O1HAmci03TYjJI7DQtzz33HEVFRVVTtaxZs4aFCxfaNC3G1IFN02KaHZumxZj0sWlaTLNj07QYkz6+p2kxJptEpmkxxqSGnyHFxhhjTK2sUDHGGJMyVqgYY4xJGStUjDHGpIwVKsYYY1LGChVjjDEpY4WKMcaYlMmo9VJFJBd4ALgQl/a5wHWqWt6oCTOmnixvm2yRUYUKcDcwGDgHyAfmAOW4qWSMyWSWt01WyJjmLxEpBMYAE1T1XVVdBIwFrhCRAxo3dcbUneVtk00yplABjgdaANFrvC7yth3fKCkyJjUsb5usEQiH460Q3PSIyE+AOaraMmb7TuASVZ2f7LGWLFlSCQSCOTkk8/4DgUDVOsoBIByuTBA/hzBQWVm5b/bbBPsQcPEqKxPEM40iJyfH++xrjxcIQMh9huE+ffokddOWjrydbPy6SjpfQ1Xejkjm+oH9r5/KBPvkxN2n9g8rx1tG2q4532rN25nUp1IE7ImzfQ9Q4PNYlUBOqLJyW1Kx/Ra8URdA0hk2mYvTNJrkP0cAWuPyWLJSnreB5PJ2Hfn6IvaZt8N1uH4q67RPZtxQNzEJ83YmFSq7iX+BFQC7/ByoT58+mfS+TfazvG2yRib1qXwFtBCRVpENItIad5f3daOlypj6s7xtskYm3dV8COwEBgAvedtO9bZ92FiJynQi8jlwaA3BeapaUcu+twFnqeqJ3tLTrwGtVHVHTfuYuCxvJ0lEXgTKVfX8qG3dgdXAO6raP2p7O6AEt2LtHap6YJLnOBUoVdWlKU18M5ExNRVV3Q08BswUkQEicgrwO+AhVS1r3NRlvJuAzrE/tRUoJnUsb/vyOnBSzLYf4mp73/dqeBH/hVv+fC5wtM9zdK17Epu3TKqpANwAHAC8AFQAfwJubtQUZYftqrq+sRPRzFneTs7rwL0icoiqrvW2DQT+CFwBnAb81dv+X8C/VHU7sL2B09lsZVShoqp7cBnnisZOS3MhIuOAK4HDgB3Ai8CV1sSVWpa3k/Zv3Mi2k4C1IhIAfgDMAgRXa4kuVF4VkUuA+1X1QBE5DFgD/BS4E+gGLAauUFX1moMBXhCROap6iYgcCcwATgE2As8Ak1R1j9fs+yyuULsMeFpVL0/f22/6Mqb5yzQ8ERkG3AaMB74DXAKcCzTri8Y0HlUNAW8Dfb1NvYCWwLvAq8AZUDWX2ve8bfHchsvHp+Oae+/3tn/P+z0CuMab7eBlXJ/NCd72QcD0qGO1B44Eekcdp9nKqJqKSZsHRGRqzLazgHW4h+/+5m37QkQW4a992phUex03Rxq4pq+3vFrDq8AsEekCHAwEgXeAn8c5xmRVfQNARB7GNT+iqhtFBGCrqpaKyKXAXuDXqhoGVESuAN4UkeujjjdFVT9L9RvNRFaoGIApwFMx275W1d0icqKITAaOAo7BNTE82dAJNCbKIuA2rzYyEFgIoKqrRORL4GTgIOCfXh6Od4z/RP29Dcir4VzHAD2A7VHHCeBaeb4TFc8KFI8VKgagRFU/jd3otUU/gmsv/juuDfr2hk2aMdUswQ1m6I3r57gtKuxVoD/QkZqbvsDNAB2tpqltcnFNa5fGCfuafSPRdtea4mbE+lRMbX4N3KeqY1T1cWAZ7u4s7XNLGVMTb6j727gv+gpc533Eq8BxuD6X2gqVZH2My/Nfqeqn3s1XO2AqbokCE8MKFVObTcDpInK0iByDe5biaPzPR2VMqi3CdZq/7nXeRywETqx4qIAAACAASURBVAQOBN6r47F3AMd6D08+hXvWZY6IHCsi/XA19xaqWlrn1Gcxa/6K4Q1RfAl4UVVnJojbFfgtbgRJBW647QRV3VpD/MjQxP64jPsEbmhiUg8ZisjdwIWqeliCeP+Fu5OLtjN2FtwoAe/Yo4BC4B+49T2uwRUk/wJKgf/D9b+MEpGq2fii//be28s1pKs17v8V6WR9ERinqltqeS/tcP+zQbgJFh/FdbJWxsSL+7mJyM24Glcr4Hngqsjnk+izFpHHgY2qekNt5xGRtsC9uMEN+biZBa5R1SY1xUqyedtvvvb2qXPeTjZfe3Fj8/Z5IrIjkrdV9WsR+QpYo6p7RSQI/ARoJyJbgTcTHP8S3GiyKd5PxM9wIx93AH8DxsXs2kpEppNk3k42X3tx0563U5mvraYSRURycE8yD0oibhD3QbbEXXzn4Na+mFND/Dzcl/UWoA8wDLgImJRk2voAv0kmLq42sZz9n5DvES+idyF3wTUlXOS9l6OAWeqcoqpFqtpZVUeo6k1Ad6o/gf8P4J94naY1mIkbAjrI++kFzE7wXhbghnKeC5wPDAXuio5Q0+cmImOAq733drr3f5ld2z5R+96EK2QTngd353q8l8bTcBf5X7080iQkm7f95mtvnzrnbZ/5GpLI26oqqhp5n3fhai4/8t5PN2C+qn4UFf+JqClcnqHmvN1SVQ9U1UsihYWqvq6qAeAe/OXthPkaGiZvpzpfW03FIyI9cBdON6DGO7IoJ+A6CjtHnkYXkauBt0SkTZy7ui64h6wuV9VtwH9EZD4uQ9yaIG35uDu/d6h5nq5oxwArknlK3qs9XAv8QlX/z9s2DnhURPJUdW/sPt60IrujjnGe9z6OSXBneg7uwckl3n734+7QakrbCbg5sHqr6gfetsuB10TkTlXdleBzm4C7+3vZ23cksExETsbdhVbbR0Q6Ao8D/XBTf0S2xz2PiByIu+j6qur73rZR3r7H0gTm7vKZt/3ma6hj3q5DvoYsyNvJ5GtvW9rzdjrytdVU9umLuwPqjWvqSWQNMDgmc0eagQpjI6vq56r6c++iQ0R64+5QkulM/G/gUyDZxZqOAT5JMu4A3PoIL0al9TVVPTLeRRfLG9Y5FXgwiXH6m4ELRaTYu+B/gfsyqskRwO7IhedZiuvTOdF7HfdzE5GDcHewVaspqupy3N30z+Pt4zkGN6XHccAXUdtryh+7gSFeuiIiTRhNZSlgP3nbV76GeuVtv/kasiNvJ5OvoWHydsrztdVUPKo6D5gHUMO49tj4m3DV4mjjgE8T3UWJyApcdXUJCZ7A9S7Qy3DV6aEJE+YcA+wQkQ9xT/suwrWJx0vXEcBa4CwRuRXogHtf45PsiByKu8u5N4m4V+Am99uC+6L6HNcGX5NvgQNEpL33/8Y7F7gho7V9bl2837Htv98Aa1X1vjj7oKqv4dqO9wur6TyquhM33DraeNyzD8tqeW8Nxk/erk++9o6fVN6uY76G7MjbCfM1NEzeTke+zpjlhFNpyZIlFdSyOt6uXbta5+XlleXl5cWOZa/R3r17C8rLywsLCgp25ubm1to5GQqFgkCgvLz8gEAgUFlYWLgzXrxwOExZWVmr3Nzcsry8vL179+7N37t3b2FRUVGNq/qFw2F27dpVHAwGK/Ly8sq88xQCgcLCwu2BwP6jgcvLywsqKioKA4FAKD8/vwwIe+kK15SuaGVlZS0DgUCooKAg4Tj9vXv35odCoXwvXZSXlxcGAoFwQUHBzth0Rd7L7t27W+Xk5FQdf8+ePUWhUCi3oKBgV25u7n53m9GfWygUCpaVlbUsKioqjT727t27WwaDwb35+fl7YveJPb8Xt8L7v8Q9T+w+FRUVeTk5OUVA5fe+970G71NJdd72k68hubxdl3wd2S8b8rbffA0Nk7cT5es9e/YUFRUVhQOBQGVti8E110LFrVEfbDL9qCaLhEIh8LFGfSpZ3jbplEzebq7NX9uCwWDx8ccf39jpMFlo6dKlhEKhtK4RXwvL2yZtksnb1lFvjDEmZaxQMQAsXryYYcOGMWzYMBYvrm1AlklGZWVlQERs5gFTo0y95hJ1mVihYgiHw0yfPp0NGzawYcMGZsyYkTDjmNrt3r27Nd7aHsbEyuRrLhQK1dptYoWKoaKigm+++abq9bp166iosOXp66NFixalum8dGmP2k8nXXKJRgFaomAZTl+p+pjYRGNNcWaFiGkRdqvuZ3ERgTHNlhYppEHWp7mdyE4ExzZUVKqbOrGnKGBPLChVTJ9Y0ZYyJp7k+UW+AHeVlrC7dELdJaXnJl+Tm5tKjuCMt86tPTltT01ReXl5a02yMadqsUGnGVpdu4Ma3niEcqrbYHLe8PZ9AMIcpJ/+cXh0OqfM5dpbvZU3pDioqqs80vqJkC7m5eXQvbkmLfCuMjMkGVqiYtFpTuoNbFv2bcChULezWN5YSCAaZfGpvju3Qtmr7rvJKvi4tj1sQfVpSRm5uiC7F+RTlW+utySzNIW9boWJ82VFezprSLXGbzD4q2UBubi7di9vSMj+/zuf4urSc3721kcpQ9XM89HYJOcFcxp7cge90iLtmlDFNVnPI21aoGF/WlG7hxkX/F7fmccsbCwkEg0w59Yf07NCpEVJnjGlsSdexROQQEam2kpKIBEWkT2qTZbJOTg6B1m2qXgZat4Wcxq/ir1u3Lu6otVAoxEcffdQIKTIms/m5qtcAB8bZfgjwZmqSY7JVIBCgcMAgAq2KCbQqpnDAmcRb7XG/fXKC5LXuUPU6v7gjgZzULj41cOBAtmzZUm37unXrGD58eErPZUx9ZMpzYbU2f4nIKNzaywAB4GURiW0MPAi3HrPJVDkBAq0PILzNrZoaKC6CnNq/8F3NoxXhbdvdPq1bJax55B7Sg5YX/TrpZAUCAQ4+9WLWvf4EAJ1PGZGwIErGs88+y9NPPw24521Gjx5N7EqJJSUldOnSJd7uxjS46OfCAGbMmMGTTz6Zkush1RL1qTwDdMUVKCcCC4EdUeFh7/WzaUmdaRCBQIDcU49m7+srAMg95buJaxGBAHkD+rH3jXcAyBvQLy0ZvOWhPTly5AMpPeaQIUNYv349AB999BF9+/alRYsW+8Vp0aIFZ555ZkrPa0xdZdJzYbUWKqq6E7gDQEQ+B55W1T3pT5ZpaMFDOxAceZq/fQ7pSvCin6UnQWlUVFTEVVddBUCXLl348Y9/TH49RqsZ41ekaXfvto1Aepp2G0vSo79UdY6InOB1yufhai/R4Q8nOoaIdAV+C5wOVAAvAhNUdauItAYeAs4GyoCHgTtVNeztmws8AFzopXsucJ2qlif7HoyJdf7557Ny5UpWrFjB3r17q3XaW7+KSYd0Ne02BUkXKiJyM3AnsBnYHhMcxhUCte0fBJ4HNuAKlQOAR4A5wLnAbKAbcJr3e453rpneIe4GBgPnAPleeDlwXbLvwZhYjzzyCNOnT6e4uLhaE1ggELBCxaRNOpp2mwI/z6n8EpikqnfV8VwnAL2Bzqq6HkBErgbeEpFDgaHAcaq6HFgqIrcC44CZIlIIjAGGqeq73r5jgf8RkUmquruOaTLN3Pz587nmmmu48sorGzspxlSzt7ySbVtDcZ/A37xxL7m50LpNkLwm9AS+n5S0B/5cj3OtAQZHChRPpK2hH1DqFSgRi4AeItIZOB5oAbwRE97CCzOmTrZu3crgwYMbOxnGxLVta4j3Xytl8evbqoUtfn0b779Wyrat1R9Ebkx+airPAsOB2+pyIlXdBPwjZvM44FOgC/B1TFhkqENXL3ynqpZGHW+biOzywn0LhUKoal12zQrdunVLOu6uXbv48ssvfe/jx/7nSO5eJ7JPffTt25c//vGPXHjhhfU6TklJCbNnz2b58uXk5OTQq1evA95888021l9omhs/hcpu4EYR+SmwCtefUUVVfQ0DEpGJwE9wF1pvIHZUWeR1AVAUJzwSp8DPeY2JVlBQwLPPPsvbb7/NwQcfTG7u/pfExIkTEx4jFApx1113UVxczF133cXWrVt5/PHHg1h/oUmRnJwgxa06Ubr9WwDatO5EThMdLeanUCkC5qXipCIyCTdU+RpVfVFEvkv1wiHyeheuQItXeBR44b4Fg0FEpC67Zo+dyUUrKira97/aGTtGo+Z9XPzkRqDvf44y//vUUWFhIeecc06N4ckcf/ny5Xz22We89dZbdOjQgaVLl3LxxRfvvvPOO8+x/kKTCoFAgB+ePIr/fXM2AAP7j2qyo8X8DCm+NBUnFJEHgauBMar6iLf5K6BzTNTI63W4u7cWItJKVbd7x2mNK+him82MSdqUKVPqfYyuXbvy2GOP0aHDvilloi74mvoLZ3j9hYdSe3/hu/VOoMkK3bsdz2UXzkwcsZH5GVI8pLZwVX0piWPcAYwFRqrq3Kigd4B2InK0qq70tp0KrFbV9SJSiruvHgC8FBW+E/gw2fdgTKxFixbVGn7qqacmPEbbtm055ZRT9tv20ksvFWD9hSaK3/5CJ7kn5lPRv5iMUJzZyWP5af76Ww3by3A1jVoLFRE5AbgZuB/4XxE5KCp4HfD/gCdF5HJcLeV2Lz6qultEHsM1F4zEPXj5O+AhVU2urcSYOC6//PK42wsKCjjooIOSKlRiPf/88yxZsiQPuBbrLzTNjJ/mr/2KWO9hxsNxo1rmxt1pfz/BFdPXez/RegKjgFm4ZoBtwLSo5jGAG3APTL6Aexr/T3iFjjF19cknn+z3OhQKsXbtWu644w7OPfdc38d76KGHmDdvHhdddNHuSZMmWX+h2Z+P/kKA3TuqP59SU/yG+MyXLl2asLZS50W6VDUE/EdEJgB/BZ5MEP8W4JYEh/15Lfvvwc2YfEVNcYypr2AwSPfu3Zk4cSJjxozhvPPOS3rfu+66i7lz5zJ69GgGDhwYGR1p/YWmWUnFY5itib/OijEZa8eOHXHXWanJ9OnTeeqpp5g6dSo/+tGPooOq+gujtlX1F+L6BCP9hdHh1l9o6q0ua7DUd90WPx3198bZXAz8Avi77zMb0wTce2/1bL1jxw5efPFFBgwYEGeP6lauXMmsWbMYNWoU/fv3Z8WKFVRUVAS8fkPrLzSNoi5rsKRi3RY/zV/fiz0/7gGtGbingY3JOMuXL9/vdSAQIC8vjxEjRjBq1KikjvHyyy9TWVnJ7NmzmT17dmRza9woL+svNI2iLmuwpGLdFj8d9acnfVRjMsTcucmMManduHHjGDduXNVrrzOztE+fPm2ioll/oWkWfHXUi0hP3MitY3D9MZ8AM1T1nTSkzZgGoarMnj2bTz/9lMrKSnr06MGIESPo3bt3YyfNmIyTdEe9iAwG/o2brfhZYD7QClgkIj+qbV9jmqpFixZxwQUXsHXrVs4880wGDRrEzp07GTFiBG+99VZjJ88Y3yr3VFL2VTllX1efj7Ts63LKviqnck9l2s7vp6ZyFzBZVW+P3igit+AW73ollQkzpiE8+OCDXHnllVXLC0c8/PDDTJ8+nZNPPrmRUmZM3ZRvrGD9s5upqKyoFvbtgi3k5uRy0NB2FHbdt4R25Z4KKjbuZG+cdVvKvy4lnJtHbocW1cLi8TOk+Lu4DsRYT+M6I43JOJ999hlnn312te0//vGP+c9//tMIKTKm4VVs3MmW51ay9S8fVwvb+peP2fLcSio2JjcDrZ9CZS1u9cZYfXBLBBuTcTp37szKlSurbV+xYgXt27dvhBQZkxrBQJAORR2rXncs6kQwkP7p8v00fz0EzBKRrsA/vW39cEMf4z3DYkyTN3z4cG677Ta+/fZbjjvuOMCN3po1axajR49u5NQZU3eBQICLel7Kk8seB2B4z0sSPm8SDATpWNSWDbvcg7+ditr5Loj8DCmeISKtgBvZ9wT9OuBWVW368zEbE8fFF1/Mzp07efTRR6ueoO/YsSNjx47loosuauTUGVM/x3bsxb0/nJ50/EAgwKW9zuHxD58H4JJeZ/tet8XXkGJVvUtE7gPa4CbCa6mq3yTYzZgm7corr2T06NFs376dgoICdu3aRceOHRPvaEwWOq7jd5hxRt0XHfUzpPhgEXkDuE1VN3iT330kIgtFpEOi/Y1pir799luGDx/OzJkzad++PS1btuTss89m5MiRbN68ubGTZ0zG8dNR/zBuKu7fR22LrBUxI5WJMqah3H777RQWFvKzn/2satuCBQvIz89n8uTJjZgyYzKTn0LlNNya8p9HNqjqF8B1wJmpTZYxDeP999/n5ptvpmvXfYssdunShYkTJ9rDj8bUgZ9CZTdwcJzt7YHEa0wa0wQVFhZWzcgabevWreTkpGJlCGOaFz8d9U8Dj4nItcC/cLMU9wam4aZsMSbjDBkyhEmTJnHTTTdx7LHHEggEWLFiBVOnTmXQoEGNnTxjMo6fQuVGoB2wAIgMXK4EZuOawIzJOBMmTKC0tJSxY8dWLZOak5PD0KFDmThxYiOnzpjM4+c5lTJgpIiMBY7EraWyWlV3RMcTkV8Cz0SWRjWmKSsoKOCee+5h0qRJrFmzhry8PLp160aLFvvPczR//nwGDx5My5YtGymlxmQG32vUq+o2XPNXTaYBrwJWqJiM0bJlS3r2rHkKuylTptC3b18rVIxJIB09kf4evzQmA4TD4cZOgjEZwYa3GGOMSRkrVIwxxqSMFSrGGGNSxgoVY4wxKeN79FcSEvZoikgAeAl4MXrafBG5Gfg10Ap4HrhKVbdGhf8St35LJ9wIsytU9avUJt+Y6vxO/21Mc5WOmsoe3EORcYlIDvA7YFDM9jHA1cClwOnA0bgHKyPhQ4AHgRuAvkAe8BevgDImrfLz861gMSYJtdZUROToZA+kqiu93zVOgy8iPYA5QDdga0zwBGCyqr7sxR0JLBORQ1R1rRf+qKo+44VfCHwDnAy8mWw6jfn000+TjnvEEUcA8M9//jNBTCccDjNlyhR69uyZ36dPn6rtVgs3zUWi5q+PcM1ZNd2iRcLC7Ju6pTZ9geXAucC/IxtF5CCgB/BGZJuqLheRLUB/EfnK23dGVPgmEfkIK1SMT2eddRaBQKDGZ08iYYFAgI8//jjp41ZWVjJ58mSWLl2634OUUbXwi4FNuOUjZgNDvfBILXw08DFwH64W/n1VtQdkTEZJVKh0T+XJVHUeMA9ARKKDuni/v47Z5RugK9AWKKol3LdQKISq1mXXrNCtW7ek4+7atYsvv/zS9z5+7H+O5FplI/v49dhjjyUdN9k8sn79eh588EFKSkooKiqKDbZauGk2ai1UvPVSaiUi+UAfIGHcWkSuwj0x2/cABUmEG5O0ZJYK3rt3L5999lnSywqrKoceeig333wz11xzTdV2q4Wb5ibp0V8i0g+YhetAj72VDPs5Vhy7vd8F7D9nWAFutcnocOKE+xYMBmNrS83PzuSiFRUV7ftf7UxuSrequ/WdsfcByZyjzP8+dfTBBx9w66238tlnn1FZuf/4kkAgwMqVK5M6TnQ6Yjr0rRZuAHzXwp28pONHavo5SX4VR++T7Jd3MtMV+Rn99SCwEfgF7kv+Itx0+DuAYT6OE0+kQ7JzzPbOuIttE67wqCncmDq5++67adeuHdOmTaOwsJD77ruP8ePHU1RUxAMPPJCKU1gt3DQrfmoXvYCTVHWZt1DXt6r6PyKyAbiWeizUparrRWQ1MADXkY+I9ATaAO+qalhE3vPCX/DC2wPHAtfEP6oxiakqf/7znznqqKOYM2cO7du356yzzqJ9+/bMmTOHwYMH1/cUVgs3+/iohQPs3rE36fiRz7xsc7nvfco3lya1TzLD6v3UVCqAbd7f/wGO9/5+DTjGx3FqMgO4Q0R+LCJ9cEOP53sdmQDTgbEiMsIrcOYBH6iqtTmbOgsGg1XT2R922GF88sknAJx00km+hh7XwmrhplnxU6i8B4zxHl78EIjcwh2LW7CrvmYAjwBPAAuBlcCvIoGq+jzwG2AK8K53zvNTcF7TjB133HHMmzePyspKjjrqKN54w/Wnr1q1iry85Nqza6Oq64FILRyoXgvHXVvR4ZFa+Dv1ToAxDczvcsIvARuAx4GJXpNVJ6KefE+Wqh4W8zoMTPJ+atpnJjCzpnBj/Bo/fjyXXXYZ7du3Z+jQoTz22GMMHDiQTZs2MXTo0FSdJlIL/wJYDzxG9Vr40yKyHFgK3I/Vwk2G8rOc8GIROQwoUtUtXhPVBcCmyPh6YzJNr169ePXVVykrK6O4uJgFCxbwyiuv0LZtW4YMGZKq08wADsTVwvOAvwFjIoGq+ryIRGrhbXBNylYLNxnJz5DiV4ELVHUjVFXrHxaRDiKyRFX71H4EY5qeiy++mJkzZ9KuXTsAOnTowPDhw9m8eTMXXHABCxYs8H3MmTNnEgqFqpqErRZumpNEc3+dhnsuBeBU4DIR2RET7bvA4alPmjHp8d5771V1wi9evJhnnnmm2lPwq1evZu3atfF2N8bUIlFNZRNwHW5+rwBwFRCKCg/jnlOZkJbUGZMGbdq04Q9/+APhcJhwOMyf/vQncnL2jVkJBAIUFRUxceLERkylMZkp0TQty3FTTCAir+Gav7Y0RMKMSRcRYeHChQCMGDGCmTNnUlxc3MipMiY7+OmoPx1ARAbinkvJwc2oulBVK9KTPGPSa+7cuQC8++67rFq1isrKSg4//HD69etHbm461rAzJrv56ajvhFsHojfwOa457FDgExH5oapuSEsKjUmjkpISxowZw8qVK+nSpQvhcJh169bRvXt3nnjiCdq3b9/YSTQmo/h5+HEG7qn67qp6pKp+BzgM2AxMS0PajEm7yZMnEwwGWbhwIS+//DKvvPIKCxcupE2bNkyZMqWxk2dMxvFTqAwCrlbVqqkjVHUdrpM+ZQP6jWlIb775JrfccgudOnWq2tapUycmTpxY9XS9MSZ5fgqVMtxor1jJrvpoTJNTUFAQd5K8QCBAKBSKs4cxpjZ+CpVXgGle3wpQ1c8yzQszJuP079+fKVOmUFJSUrWtpKSEqVOn0r9//0ZMmTGZyc/wlt8ArwJfeHMYgeuoX4Zbf9uYjHP99dczcuRITj/9dA4++GAA1q1bh4ikaj0VY5oVP4XKPNxT9d/HDSnejRtSvAz4O25JYWMyyoQJE3jqqadYtmwZq1atorCwkMMPPxwR4Ve/+lWdpmkxpjnzO03Lpbgn6CNTtRwJnItN02IySOw0Lc899xxFRUVVU7WsWbOGhQsX2jQtxtSBTdNimh2bpsWY9LFpWkyzY9O0GJM+vqdpMSabRKZpMcakhp8hxcYYY0ytrFAxxhiTMlaoGGOMSRkrVIwxxqSMFSrGGGNSxgoVY4wxKWOFijHGmJTJqPVSRSQXeAC4EJf2ucB1qlreqAkzpp4sb5tskVGFCnA3MBg4B8gH5gDluKlkjMlklrdNVsiY5i8RKQTGABNU9V1VXQSMBa4QkQMaN3XG1J3lbZNNMqZQAY4HWgDRa7wu8rYd3ygpMiY1LG+brBEIh+OtENz0iMhPgDmq2jJm+07gElWdn+yxlixZUombdbnZiszKW5ng88/xltqtrKz0vU9EZYIsluNF33eOQJLnCFNZWVn7wRtPuE+fPkndtFnebh785m0nQKLv6EDUtZCTk0MgyX3C++0DiYqCQABC7nqrNW9nUp9KEbAnzvY9QIHPY1Xiamnb6puoTJXsl3H0BVCXfZKLX5d0+TpFQ2uNy2PJsrzdDKQrb4frcP1Q930S5u1MKlR2E/8CKwB2+TlQnz59Mul9m+xnedtkjUzqU/kKaCEirSIbRKQ17i7v60ZLlTH1Z3nbZI1MKlQ+BHYCA6K2nept+7BRUmRMaljeNlkjYzrqAUTkt8C5wEhcZ+STwDOqauu+moxmedtki0xrf70BOAB4AagA/gTc3KgpMiY1LG+brJBRNRVjjDFNWyb1qRhjjGnirFAxxhiTMlaoGGOMSRkrVIwxxqSMFSrGGGNSxgoVY4wxKZNpz6mknYgEgJeAF1V1ZoK4XYHfAqfjni14EbcmxtYa4h8JzAD6AzuAJ4BJqlqRZNruBi5U1cMSxPsv4O2YzTtjZ8GNih8E7gRGAYXAP4Axqrq5hviXAH+s4fSnquob8QK8qUd+i1uICtz/a5yqbqnlvbTD/c8G4SZYfBSYrKqVMfHifm4icjPwa6AV8DxwVeTzSfRZi8jjwEZVvaG284hIW+Be4CzcAluvAdeoapOaYiXZvO03X3v71DlvJ5uvvbhZkbeTzdde3LTn7VTma6upRBGRHOB3uA86Udwg7oNsibv4zsGtfTGnhvh5uAy9BegDDAMuAiYlmbY+wG+SiQscDSwHOkf99Kgl/l3ApV56TgeOAmbVEv+ZmGN3xr23fwLv1LLfTKAX7v87yPt7doL3sgA4Afe0+fnAUC+9VWr63ERkDHC1995Ox/1fZte2T9S+N+G+iBKeB/cldLyXxtNwF/lfvTzSJCSbt/3ma2+fOudtn/kasidvJ8zX0DB5O9X52moqHhHpgbtwugE13pFFOQHoDXRW1fXeMa4G3hKRNnHu6roAi4HLVXUb8B8RmY/LELcmSFs+7s7vHeDQJNJ2DLAikq4Ex24NXAv8QlX/z9s2DnhURPJUdW/sPqq6GzezbuQY53nv45gEd6bnAFeq6hJvv/txd2g1pe0E3BxYvVX1A2/b5cBrInKnqu5K8LlNwN39veztOxJYJiInA1Pi7SMiHYHHgX64iR4j2+OeR0QOxF10fVX1fW/bKG/fY2kCc3f5zNt+8zXUMW/XIV9DFuTtZPK1ty3teTsd+dpqKvv0xd0B9QZKk4i/Bhgck7kj0xMUxkZW1c9V9efeRYeI9MbdobyaxLn+G/gUSHaxpmOAT5KMOwC3PsKLUWl9TVWPjHfRxRKRXGAq8KCqfpYg+mbgQhEp9i74X+C+jGpyBLA7cuF5luKmhD/Rex33vbM53QAAB5ZJREFUcxORg3B3sFXNFaq6HHc3/fN4+3iOAbYDxwFfRG2vKX/sBoZ46YqINGE0laWA/eRtX/ka6pW3/eZryI68nUy+hobJ2ynP11ZT8ajqPGAegIgkE38TrlocbRzwaaK7KBFZgauuLgHuTxC3N3AZrjo9NGHCnGOAHSLyIdAetzTthBrSdQSwFjhLRG4FOuDe13hVTaZwHYq7y7k3ibhXAHNxmT8MfI5rg6/Jt8ABItLe+3/jnQugI9T6uXXxfse2/34DrFXV++Lsg6q+hms73i+spvOo6k7g7zHnGI9bJGtZLe+twfjJ2/XJ197xk8rbdczXkB15O2G+hobJ2+nI11ZTSRERmQj8BFfdTmQEcAZuvYwFtRwz0jzwm2QuaG+fYuBgIA/4Ja4tuTvwD6/tO1YrL/5/4zLNhbi7lv9J5nzAGOCJmjo+Y3wH+BgY6P1sBZ7yOgnjeQ9YDcwSkTZe5+Y0XOdxfoJzFXm/Y1dUrMtqikkTkV/g/o83RJoxMpnPfA1J5O265Gtvv2zJ2/XJ19AIedtPvrZCJQVEZBKumnytqr6YKL6q/ttr470EOENEjqkh6iTga1WtsZM0zrFLgWLgPFVdrKqv45oieuLacWPtxV18l6jqq6q6CBgNDBaRI2o7l4gcjGtiSJg+71i/Ay7zmiBeBy4AflBDulDVPV6cY3DNC18Ar3t/J1ouN9IuHnuR+V5NMVneyKGncM0lj6TjHA3Jb76GpPO273ztHTsr8nY98zU0cN72m6+tUKknEXkQuB03THFGLfG6isgFMZs/8n53qGG3i4DTRWSHiOwAHgAO8V4PqGEfVHWbqoaiXn8LbAK6xom+zvu9Imrbx97vRJ2nQ3Add7X1i0T0Bvao6n+i0vUFUEIto3dU9UNVPRo4CPd/egTXRLA6wfkineydY7Z3Jg2rKXodwH8E7lPVCak+fkNLNl97cf3m7Trla8ievF2PfA0NmLfrkq+tUKkHEbkDGAuMTKIEF+BZcc8ARHwP1/76cfxdOA030uJ472cK7kI5HvhXDWnq+//bu58Qq8owjuPfNmomlKi4CMYRgicoCayskMRFLcKiRRCIiyCwlTAQKE3TJnHRJoUJqQwdSyjpD0H/ICWoMahEtEC0J/sztohIQcmwYTJq8bynjnfumTn3zjvX6+X3gWGYM2fOeZl55j7nnvc9z2NmF8ysr7StD1hccZ5imeTK0rbi6nK6AL8HGHX3Ov0TfgHmWTzPUIxrKXFfvOkkqJktNLNDZrbM3X9z93FgHXHvuOp3BkC6rfIjpW6KZrYCuAH4osZ4a0urYrYDz7j7YM5jXwktxjW0HttraTGu07h6IrZnEtfQudhuN641Ud+mtCxwiJiMPJhWZBTONll+OEosw3stLdFcAuwCdqWrrUnS1U75nGeBS+7+/RRDO0YE+R4ze5JYsTMMfOruXzU5xw9m9k7afyMwkcb1kbv/NMV5ICZZK+eEGnxJTN7uMbMBYiXJ88SLyKFmP+Du58xsHrAj3dtfDuwkgrzOP/swsNXMTgO/Aq8Ab7n7zzXHPK30d3+BuE+/uyEOzqVbHVeNNuIaWoztNuMaeiS2M8Q1zHJszySu9U6lfY8Qv78txBVG+ePmxp3TEsaHiNUhnwNvEksdB3IOKv2xHyCeav4MOAB8x9QrbB4jgv9DYhnocWJSczpLifvAdcZ1ibgaGyOe3P2YeIFY502eIi55FLiOeEF5CXjW3SufbWkwTNxW2At8ApwANtb82boeJCZO1zM5Du7PfK5OaCmuQbHdZmzPJK5h9mO77bhW50cREclG71RERCQbJRUREclGSUVERLJRUhERkWyUVEREJBslFRERyUZJRbIxs34ze7j09ZiZbbqSYxLJQbFdn5KK5DRCqXSESA9RbNekpCI5VZWwF7naKbZr0hP1PczM/iHKLAwSRf+OEBViNxN9L34HBt19X9r/emAbUZZ7IVHTacDdPX1/DNhBlBtfRXTtG3L3981sL1ESA+C0u/en/d8l6iitJiqoPuXurXT6E5lEsd299E6l9z1HNFi6G+gDjhL/cHcSBfNeNrMFad+3iX7c64G7gHHggJnNLx1vK1Gr6A7gFDCSmi4NEBVSX0zHLjxB9MW+BTgI7LNotyoyU4rtLqSk0vt2psZBXwMfEMX4nk5XaNuJftPLzexW4D6iodGoR8/rDUTRuw2l473h7vvd/QTRb2MR0J8aKE0AF939TGn/3e7+ukeP721EI6GmhQlFWqTY7kJKKr2vXE78IjBWKq89nj7PJa62JogS3sB/faqP8X8PCoiqsIWiS12zVq6Fcj+J8+nztbVGLjI1xXYXUlLpfX81fF1VivvPiu3XcHmcTFTsU+XvJts06Sk5KLa7kJKKFE4Cc4Dbiw3pfvNtwLc1j6FVH9KNFNsdpKQiALj7KWJyc8TM7k33oV8lrsb21zzMH8BNZnbjLA1TpGWK7c5SUpGyx4HDwHtEi9T5wBp3r9UBj1gdsxr4xswUW9JNFNsdoudUREQkG2VcERHJRklFRESyUVIREZFslFRERCQbJRUREclGSUVERLJRUhERkWyUVEREJBslFRERyeZf7RIUchMqx/UAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_col_list = ['month','weekday','total_count']\n",
    "plot_col_list= ['month','total_count']\n",
    "spring_df = hour_df[hour_df.season==1][df_col_list]\n",
    "summer_df = hour_df[hour_df.season==2][df_col_list]\n",
    "fall_df = hour_df[hour_df.season==3][df_col_list]\n",
    "winter_df = hour_df[hour_df.season==4][df_col_list]\n",
    "\n",
    "fig,ax= plt.subplots(nrows=2,ncols=2)\n",
    "sn.barplot(data=spring_df[plot_col_list],x=\"month\",y=\"total_count\",ax=ax[0][0],)\n",
    "ax[0][0].set(title=\"Spring\")\n",
    "\n",
    "sn.barplot(data=summer_df[plot_col_list],x=\"month\",y=\"total_count\",ax=ax[0][1])\n",
    "ax[0][1].set(title=\"Summer\")\n",
    "\n",
    "sn.barplot(data=fall_df[plot_col_list],x=\"month\",y=\"total_count\",ax=ax[1][0])\n",
    "ax[1][0].set(title=\"Fall\")\n",
    "\n",
    "sn.barplot(data=winter_df[plot_col_list],x=\"month\",y=\"total_count\",ax=ax[1][1])  \n",
    "ax[1][1].set(title=\"Winter\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Year Wise Count Distributions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1d380ab0e10>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sn.violinplot(data=hour_df[['year',\n",
    "                            'total_count']],\n",
    "              x=\"year\",y=\"total_count\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "+ Both years have multimodal distributions\n",
    "+ 2011 has lower counts overall with a lower median\n",
    "+ 2012 has a higher max count though the peaks are around 100 and 300 which is then tapering off"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Working Day Vs Holiday Distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1d380d6f4e0>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,(ax1,ax2) = plt.subplots(ncols=2)\n",
    "sn.barplot(data=hour_df,x='is_holiday',y='total_count',hue='season',ax=ax1)\n",
    "sn.barplot(data=hour_df,x='is_workingday',y='total_count',hue='season',ax=ax2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Outliers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1d380e7a588>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,(ax1,ax2)= plt.subplots(ncols=2)\n",
    "sn.boxplot(data=hour_df[['total_count',\n",
    "                         'casual','registered']],ax=ax1)\n",
    "sn.boxplot(data=hour_df[['temp','windspeed']],ax=ax2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Correlations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1d380f7bcc0>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "corrMatt = hour_df[[\"temp\",\"atemp\",\n",
    "                    \"humidity\",\"windspeed\",\n",
    "                    \"casual\",\"registered\",\n",
    "                    \"total_count\"]].corr()\n",
    "mask = np.array(corrMatt)\n",
    "mask[np.tril_indices_from(mask)] = False\n",
    "sn.heatmap(corrMatt, mask=mask,\n",
    "           vmax=.8, square=True,annot=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "+ Correlation between temp and atemp is very high (as expected)\n",
    "+ Same is te case with registered-total_count and casual-total_count\n",
    "+ Windspeed to humidity has negative correlation\n",
    "+ Overall correlational statistics are not very high."
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
